Table of contents

International Virtual Conference on Intelligent Robotics, Mechatronics and Automation Systems (IRMAS 2021)

March 26-27, 2021

Mechatronics and Robotics deal with the synergistic incorporation of diverse disciplines, such as mechanical engineering, electrical engineering, manufacturing engineering, computer and software to solve complex problems. Intelligent Mechatronics Systems transform world towards complete automation. The transformations include industrial automation (Industry 4.0), smart manufacturing systems, connected machines, Intelligent and autonomous vehicle technologies, autonomous and service robots, etc. These technological developments drive us into the future where almost everything will be automatic.

The conference is jointly organized by the Centre for Automation and School of Mechanical Engineering, Vellore Institute of Technology (VIT), Chennai, India in Virtual Mode. This Virtual Conference received overwhelming response from Participants from all parts of India and many other countries Malaysia, Bangladesh, Indonesia, Turkey and Morocco. Out of the 140 papers received, 110 papers been accepted after scrutinizing and peer Review process. This includes 20 Papers from outside India.

Due to the current pandemic situation, which made situation not suitable for transport and gathering, the conference has been organized completely in Virtual Mode. The entire conference is conducted using video conferencing platform-Zoom. It enabled all the speakers to present live for the audience and answer all the questions posted to them in an efficient way. This virtual conference enabled the researchers and students to present their work from their home/workplace in the testing time due to the pandemic. A total of 127 participants has participated in this two-day conference.

The conference hosted four keynote lectures each spanning 60 minutes each including live Q&A sessions. A total of 110 papers has been presented in 14 sessions across two days of the conference. Each paper has been allocated 12 Minutes for presentation and 3 minutes for Q&A. Among the presented 110 papers, 71 papers have been scrutinized for publication.

List of Keynote Speakers, Convenors, Organizing Secretary, Organizing Committee, Technical Committee are available in this pdf.

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

• Type of peer review : Single-blind

• Conference submission management system : EasyChair

• Number of submissions received: 140

• Number of submissions sent for review : 138

• Number of submissions accepted : 67

• Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100) : 48.55%

• Average number of reviews per paper : 2

• Total number of reviewers involved : 23

• Any additional info on review process : Plagiarism check has been conducted for all the process. Based on the check, papers with more than 20% similarity has been sent back to the authors for modification.

• Contact person for queries:

Name : Dr. D. Saravanakumar

Affiliation: Centre for Automation, Vellore Institute of Technology, Chennai, India.

Email : saravanakumar.d@vit.ac.in

In this paper, an effective and simple Grid based vanishing point detection position estimation algorithm and Enhanced GIST descriptors based indoor scene recognition algorithm for navigation of MAV in indoor corridor environment is described. Two different classifiers, k-nearest neighbour classifier and support vector machine is employed for the categorization of indoor scenes into corridor, staircase or room. Indoor scene classification was performed on Dartaset-1. In the training phase of the indoor scene recognition algorithm, GIST, HODMG and Enhanced-GIST feature vectors are extracted for all the indoor training images in the Dataset-1 and indoor scene classifiers are trained for the extracted image feature vectors and assigned image labels of the indoor scenes (corridor-1, staircase-2 and room-3). In the testing phase of the indoor scene recognition algorithm, for each unknown test image frame GIST, HODMG and Enhanced-GIST feature vectors are extracted and the indoor scene classification is performed using a trained scene recognition model. The proposed indoor scene recognition algorithm using SVM with Enhanced GIST descriptors produced high recognition rates of 99.33% compared to the KNN classifiers. After recognizing the indoor scene as corridor, the MAV has to estimate its position based on the detection of vanishing point in the indoor corridor image frames. Experimental results show that the proposed method is suitable for real time operations.

Robotic systems are known for their precision and accuracy. To achieve a desired set of operating parameters the system must have a good control system. Robotic arms can vary in size shape and purpose of use. With increasing DOF (Degree of Freedom) the complexity of the system increases and hence a DAQ system is required to check various parameters of the process. This paper discusses the implementation of kinematic and inverse kinematic modelling of a 6 Degree of Freedom (DOF) hydraulic arm in MATLAB environment. The forward kinematic model is based on Denavit-Hartenberg parameters. To obtain a given set of position and orientation of end effector, inverse kinematics gives the required set of joint angles. Potentiometers mounted on arm joint are used as the prime feedback elements for extracting the joint angles. All six joints of the arm are revolute joints. The values of potentiometer obtained are compared to the desired input values. Proportional direction control valve is the main controlling element of the hydraulic circuit. The forward and inverse kinematics is validated and implemented in MATLAB robotics toolbox (developed by Peter Croke). A GUI is also used to ease the process of retrieving and feeding the information in the system. The results of forward and inverse kinematics from MATLAB are verified by the physical model discussed in this paper.

A quadruped walking robot has an advantage on uneven terrains. In a real-world application, robots can carry heavy loads and can scout in a dangerous area. The main disadvantages of walking robots are relatively slow and high energy consumption. In recent years developed quadruped robots are mimicking several kinds of mammals. Bio-inspired mechanisms are helping to improve the overall performance. The implementations have reduced energy consumption, enhance stability, and a more comprehensive range of locomotion—this article introduces a quadruped robot with passive-compliance three segments' legs. The leg compliance is implemented by adding an elastic spring to the leg. From the experiment conducted, the fabricated quadruped walking robot's average walking speed is 0.06850 m/s.

This article introduces a 4-legged walking robot using Hoeckens Linkage. In some applications, a legged robot is preferred if compared with a wheeled robot because it has a more considerable degree of freedom and can move on uneven surfaces. Hoeckens Linkage is one of the linkages that can convert rotational motion to approximate straight-line motion, which allows the robot to move faster than other linkages. This robot is designed using SolidWorks to simulate the Hoeckens linkage path, and its structure is built using 3D printed parts. Arduino Mega was used as a microcontroller to process the feedback signals so that the robot able to move in the desired pattern. The hall effect encoders were used so that DC motors always rotate with the desired RPM regardless of walking surfaces and power supplied to them. MPU 6250 gyro sensor also be used in this walking robot as a navigation sensor. Gyro sensor allows the robot to travel in a straight line or rotate a certain degree by computing yaw value from its raw data and DC motors' control speed using a P controller. The speed average of the fabricated robot is 3.00 m/min.

In our previous work, we focused on the development of Razbot, a hexapod platform, and achieving its autonomy using the Robot Operating System (ROS). Therein, we also explained the difficulties faced with Razbot while trying to execute complex operations autonomously. Hence, in this work we address the problem and make an attempt at improving the odometry measurements of Razbot by introducing a Visual Inertial System (VIS) that includes a pair of synchronized monocular camera and inertial measurement unit which makes it capable of mapping the environment and autonomously navigating in it with increased effectiveness. To introduce the VIS, we made minor modifications in the components used and the control scheme of Razbot. In this work, we take help of the Extended Kalman Filter (EKF) for the fusion of odometry sources. Further, we also analyse the accuracy of the fused odometry by comparing the same and evaluating the errors or drifts in odometry before and after introducing the VIS in Razbot. Based on these results, we make a conclusion that the odometry source from VIS can significantly lower errors and drifts in fused odometry data, thus improving autonomous navigation and mapping of the hexapod robot. The implementation of this system will allow Razbot to be used in even more varied applications than those specified earlier.

Nowadays, for precision positioning applications (Micro-Electro-Mechanical Systems, Nano/Micro positioning devices), compliant mechanisms are extensively used over traditional mechanisms. Compliant mechanisms are joint less mechanism having merits as no wear and friction, no backlash and no lubrication. In this paper, a newly developed flexure hinge based bridge and lever type compact compliant mechanism has been proposed for the precision linear displacement applications. This mechanism can be used in the portable cameras for image stabilization, lens shutters, alignment and levelling devices, etc. The key performance parameters for developing the compliant mechanism are the input displacement/force, output displacement and amplification ratio. For designing compact amplified compliant mechanism (CACM), Pseudo-Rigid-Body-Model (PRBM) method is used. The finite element analysis of developed micro-displacement amplifier compliant mechanisms carried out by using ANSYS workbench. The analyses and experimentation is performed for the input displacement, output displacement and amplification ratio of mechanism. An input force range considered for analysis is in between 1 N to 50 N. All the results from analytical, simulation and experimentation are compared. The error in output displacement is observed up to 6% and the geometric amplification ratio for the mechanism is observed up to 6.5.

Automated Cartesian coordinated farming is a system designed for agricultural purposes. Being one of the trends of development on automation and intelligence in the agricultural machinery, this system is able to perform certain basic elementary functions like seed sowing, spraying, watering, etc. The idea of robotics technology is being applied in agriculture. This is being designed in minimizing the labor of farmers apart from increasing the speed and accuracy of the work. A scalable Cartesian coordinate based system is modeled, which can take care of a particular area of farm land or a garden until it is time for harvesting. The system starts by planting individual seeds at predetermined locations and then automatically waters it with the exact amount required for each type of plant. It has the ability to measure soil humidity and rainfall so that water can be used depending upon on the nature of the day. The proposed system makes use of a YOLO (You Only Look Once) object detection technique to detect weeds. YOLO processes plant images at 45 frames per second in real-time, which is faster than other object detection techniques. Here, the image is divided into several grid cells before being processed. The bounding boxes as well as the class probabilities are predicted by one single neural network, in a single evaluation. This effectively boosts the speed and accuracy of weed detection.

Nowadays, climbing robots are widely used in industrial and hazardous environments for inspection purposes. On the other hand, the Pole climbing robot can help workers fix maintenance, power transmission, etc. This article aims to design and fabricate an autonomous pole climbing robot, which can climb upward/downward a pole. The robot has two grippers at the top and bottom of the robot body, climbing along a pole by alternating release/grip mechanism. The robot body and robot grippers are fabricated using a rapid prototyping machine using PLA material. The prototype of the robot is tested on a pole of diameter 110 cm. The average time taken for the robot to climb 40 cm on a straight pole is 18.18 s and 17.21 s for upward and downward motion, respectively.

This paper discusses an ongoing project of building a quadrupedal robot designed for operations in rugged terrain by using Theo Jansen's linkage mechanism. The robot is unguided, but it is still able to maintain the ability to evade obstacles and change its course automatically. The robot utilizes Jansen's linkage mechanism for all four legs to mimic a four-legged animal's movement and stability. Due to the smooth motion nature, it can provide a very high degree of stability, enabling it to carry items that require a smooth and stable motion. Jansen's linkage mechanism is also easy to operate and design; a pair of legs could also be powered by one rotational movement, reducing overall energy consumption. The quadrupedal robot's goal was to maintain a smooth and stable motion even when navigating obstacles and could ensure item delivery safety. The fabricated robot's average speed is 0.02178 m/s, and the power consumption is 5.71 W.

This paper showcases the application of Neural Networks for manipulation. Algorithm based approaches work well although are limited in their ability to find solutions sometimes. The tedious task of programming a manipulator can be replaced with Neural Networks which can learn how to solve Inverse Kinematics. We present a pick and place scenario using Neural Network to solve Inverse Kinematics. Their ability to learn from examples make them a good candidate to solve the inverse kinematics problem. For this purpose, a unique configuration of 5 DOF arm is designed to suit industrial needs. To train the network, a dataset of random joint positions is created and forward kinematics is derived for the corresponding joint angles. The joint variables are then fed to a path planner in Simulink and then the process is simulated.

Flexible parallel manipulators can be used as an orienting device because of their precise positioning ability and better stiffness. The flexibility to the manipulator induces challenges in the selection of actuator, sensors and control. The paper presents a novel mechatronics design of a flexible symmetric parallel manipulator with minimum number of actuators used as an orienting device. Shape memory alloy springs (SMA) are used as an actuator because of ease of integration and higher deflection. In order to avoid any contact type sensor which could affect the compliance of the manipulator, the position of SMA spring is calculated indirectly from the kinematic model with the end effector orientation data measured from IMU sensor. The complete experimental set up design including electrical and control circuitry is explained in detail in the work. Preliminary open loop test is conducted on the prototype to understand the SMA response to various current input and to verify the effectiveness of the kinematic model in the actuator length measurement. Closed loop control based on ON/OFF control is implemented in the controller and is tested for step input.

Interest in creating legged locomotion has increased compared to wheeled robots since wheels, while easier to design and fabricate, are less effective when traveling across certain surfaces. Legged walking robots are mostly based on a quadrupedal living creature's biological concepts, whether an insect or mammal. For a walking robot, sequences of motions are understood as 'gaits' to determine the robot's mechanism. The proposed method is the creep gait, which is easy to fabricate and has allowed the algorithm's proper user control. Meanwhile, the shuffling motion ensures the maintenance of the robot's stability and vertical movement. Stability and gait-planning are also crucial in selecting the suitable quadruped mechanism, depending on the robot's application. The result is a quadruped with the lowest risk of toppling and stable carrying capacity by combining the two gaits. The robot has a linear velocity of 1.09 cm/s.

In the world of globalization & competitive market there is demand of alternative designs with improved quality, economy & safety. Emerging designs of compliant mechanisms making noticeable contribution to economize cost of production. Compliant mechanism derives their mobility through deflection of flexible members opposite to the conventional rigid body mechanism. The integration of functions into fewer parts, compliant mechanisms offer significant advantages such as fewer parts, less wear, noise & backlash. Researchers expects this field will grow enormously due to advances in the compliant mechanism theory, development of materials with superior quality & advancement in 3D printing technology in the recent years. Recently many familiar examples of compliant mechanism are used in transportation, aerospace, micro-mechanism, biomedical, hand held tools, MEMS & robotics industry. The objective of the current work is to study compliant mechanisms & their applications in various fields communicated by various researchers.

Pressure Ulcers (PU) seems to be one of the most challenging healthcare problems around the world. It may result in significant morbidity, mortality and is associated with high cost in terms of treatment and care. PU is considered to be the third most expensive disorder after cancer and cardiovascular diseases. Though, modern medical science has launched a variety of treatment methods, prevention is the best way to overcome. As it could be seen from the current market design, most of the products provide a cushioning effect to the end user, but this lacks in product customization. Further, these products are not custom made to meet the end user needs and these products are expensive to be used. Understanding the above intricacies, the current research is focused entirely to be different from the existing product design, working, manufacturing methods and materials for the development of a product to redistribute the pressure for the reduction of PU. The projected design purely depends only on mechanical materials and mechanical behaviors. In this work, the number of phases of design was carried out through Solid Works software. The deformation and stress analysis was carried for all the design phases for obtaining the better design. Finally, the prototype is developed through Additive Manufacturing (AM) technology with the multi-material combination. The final prototype was evaluated experimentally using emed® sensing platform for the flexibility and pressure distribution also compared with the existing cushions.

The present work employs an experimental and analytical method to investigate the wear of an external gear pump. The first part of experimental method involves, running the gear pump on test rig for set number of working hours and the performance curves are plotted for studying any variation during the course of experiments. In the second part of experimental method the circulated oil was studied for any contamination. Contaminated oil is an indication of wear which is to be detected using ferrography. The gear pump therefore was run for maximum number of hours to study the variation in performance of gear pump due to wear during the running operation. The oil samples were collected after the pump has been run at a set discharge pressure for a certain number of hours. Wear was expected to occur to detect the presence of ferrous particles for checking whether the gear pump components have worn out after the operation. Direct ferrogram reading machine was used to detect small and large particle size concentration and based on this the wear severity index was found out analytically. Also the necessary conclusions using graphical trend are obtained between particle size concentrations and wear severity index with respect to time.

The dynamic characterization of honeycomb sandwich structure with CNT reinforced hybrid composite face sheet is performed using Finite element simulation. The element simulations. The Potential and Kinetic energies of the honeycomb sandwich beam were derived using classical laminate beam theory and Mindlin theory. The governing equations of motion for the sandwich composite beam is made up of Nomex material with a hybrid composite face sheet reinforced with CNT are obtained by applying the Hamilton rule in the finite element model. The functionality of current finite element modeling has been investigated to proving the dynamic properties acquired from the improved finite element model with the solution obtainable in the previous literature. A further various parametric study is performed to understand the effect of CNT content, thickness ratio, and boundary constraints on the honeycomb sandwich composition of dynamic properties with reinforced CNT of the hybrid composite face sheet is performed using finite element simulation. The CNT content in the honeycomb sandwich beam containing a remarkable effect on the natural frequency.

Joining of metal is very important operation in every manufacturing activity. Conventional welding of Al alloys by Tungsten inert gas welding, Metal inert gas welding and Resistance spot welding was reported to produce poor quality weld joints, as the inherent characteristics of the base metal affected the weld properties. Friction stir welding, identified as one of the best alternative is employed to join Al 5083 and Al 6061 in this study. Aluminum alloys, Al 5083 and Al 6061 are welded in lap joint configuration, with SiC nano particles interlayer. The process parameters such as welding speed tool, rotational speed and volume percentage of Nano-powder were optimized by utilizing Response surface methodology, RSM. The joints welded without the SiC nano particle interlayer were observed to possess low mechanical strength at the best welding conditions determined by the RSM.

Traditionally welding is considered as an art rather than a science. The quality of the weld is dependent on the skill and intuition of the welder. The welding process is mostly not reliable and labor-intensive. The solution to the problems in welding lies in utilizing intelligent welding techniques where in the selection of weld parameters like voltage, current, speed etc and defect control is done intelligently by the automated welding system. The intelligent welding system shall comprise elements, viz., control system, sensing, design and modeling of process and application of artificial intelligence. The application of intelligent welding system has developed into a new field of automation called as 'Integrated Computational Welding Engineering (ICWE)'. The welding of titanium and its alloys is predominantly dependent on the skill of the welder. Majority of research and industrial practice is based on the traditional manual welding process and hence it is prone to defects deterioration of metallurgical, mechanical and corrosion properties. There is scope in adopting ICWE in welding of titanium and its alloys.

At present, the methods by which products are designed and manufactured are advancing at a rapid pace just before our eyes. The contemporary period known as Industry 4.0 is realizing an evolution from manual to digital operations and it has great importance to manufacturers throughout the world. In the context of Industry 4.0, intelligent manufacturing is a paradigm enabled for the integration of smart sensors and controls. Traditional manufacturers are exploring intelligent manufacturing approaches (Machine Learning/Artificial Intelligence, Internet of Things, Digital Twin, etc.) to improve their competitiveness, but lack in implementing them. This paper reviews the intelligent manufacturing approaches and extends a study on how a manufacturing production plant applies its intelligence in executing these approaches to transform from discrete manufacturing to intelligent manufacturing. The case study initiates the implementation of Siemens manufacturing production plant into a model based on intelligent manufacturing, thereby transforming the whole into an intelligent manufacturing industry. A broadened path about the implementation of intelligent manufacturing in this industry is outlined. In the operation of selecting these approaches, the manufacturing plant continuously mechanizes its products, informatizes its management, and digitizes its operation.

The exhaust noise is considered to contribute disturbance to large extent in any vehicle. The sound wave cancellation device is used for better noise attenuation without much compromise on engine efficiency. This paper aims to design an advanced muffler which gives considerably lower back pressure in exhaust system line, thereby optimizing the power and torque of an engine. Study includes close monitoring of parameters such as power, torque, and transmission loss within the given boundary conditions. The limiting condition laid by Formula Society of Automotive Engineer (FSAE) is satisfied using Ricardo Wave Build software.

Corrosion degradation of ship hull plates is an important aspect responsible for failure of ships in marine environment. Surface coatings are being used to protect the metallic materials from corrosion. In this work, Al₂O₃-13 % TiO₂ coating and Cr₂O₃ coating were deposited on ship hull building material using D-gun flame spray method. The corrosion behaviour of coatings and substrate was investigated using cyclic polarization test. The microstructure and phase composition of coatings were analysed by scanning electron microscopy (SEM) and electron dispersive spectrum (EDS). The corrosion rate was evaluated from the corrosion parameters extracted from graphs. The uncoated and coated substrates were compared on the basis of corrosion parameters.

This research paper aims to explore opportunities for weight and cost reduction in the design and development of connecting rods. Two phases are involved in the analysis. The first part i s t o analyze the loads (compressive and tensile loads) acting on the connecting rod as a function of time to optimize its weight and manufacturing cost using generative design. The generative design is an iterative design process that produces a certain number of outputs based on the power, stress and other constraints applied. The primary considerations are weight, material, and cost for the connecting rod design, we generate which in turn, provides sufficient strength, stiffness, and fatigue resistance. The second part involves the analysis of finite elements that was performed at several crank angles and examined whether the generated designs withstand loads ranging from the tensile load, corresponding to 360⁰ crank angle as one extreme load at the maximum engine speed and compressive load corresponding to the peak gas pressure as the other extreme load. Thus, a wide variety of materials are analyzed to obtain the cost-effective and optimum design of the connecting rod that can be manufactured by additive manufacturing.

Geometry and operating standards determines that worm drives are critical components in and of applications within the power transmission industry. In one reduction point, it is used in large drive ratios with compact assembly dimensions. Worm and worm wheels are provided with a quiet operation owing to the movement of slipping between the worm and worm wheels tooth flanks. Its efficiency depends significantly on the thickness of the lubricating film, which in turn is dependent on various operating parameters. The different researchers have performed detailed research in the field of worm and worm wheel construction. Many researchers have developed and suggested methods for the prediction of worm and worm wheel gearbox performance with respect to different factors such as tribology, analytic and geometry. This paper includes a comprehensive literary analysis to obtain thorough knowledge of trends in the fields of worm and worm gears.

Leather is a robust, durable and stretchy material created by tanning animal rawhide and skins. It is used to make variety of articles including footwear, bags, fashion accessories, furniture etc. The conventional method of cutting leather is a tiresome process. Laser diode technology offers advantages in cutting intricate geometries, stable cutting quality and potential to make the most use of leather product effectively. In this study, the machinability of leather using diode based laser beam machining and surface quality of the leather product have also been examined. The goal is to acquire the thermal effect caused by the laser at the cut contour edges. Buffalo leather has been taken as specimens in the present study. While cutting leather, it has been. proposed that diode based Laser Beam Machining minimize carbonization layer more than traditional machining.

Our research work involves the use of the use of digital manufacturing tools to develop a novel design alternative to an existing application. An everyday electric drill machine has been considered and had its functionality enhanced by redesigning its body in accordance with the solutions aimed at mitigating a few shortfalls, which primarily involves its safety aspects and ease of use, while also not compromising on its extant operating capacity as well as retaining the ability to be wielded by professionals well-versed in handling the original machine. To that end, we deconstructed the CAD (Computer-Aided Design) model of a conventional drill, and attached an auxiliary (precision) grip through generative design- a superior designing experience that is powered by Alternative Intelligence-by using Autodesk Fusion 360 software. Then, it was converted to an STL file (Standard Tessellation Language), which is a competent file format for subjecting the design to the various pre-processing steps required for creating a physical model of it using additive manufacturing. Firstly, file repair and manipulation tasks were carried out through Autodesk Meshmixer and Netfabb, with the latter also doubling up as the implement used for carrying out the printability analysis, orientation optimization, construction of support structures, and finally, slicing. The finished model was of the dimensions of 165.3820 mm x 204.4808 mm x 76.2340 mm, which indicates that the design alterations did not produce a vastly different version of machine than the original one. However, the output would be considerably efficient since the overall weight is reduced, and the presence of auxiliary handle would bestow more control on the operator. This also renders the body of the electric drill a monolith, which would enable a simpler assembly operation during the manufacturing stage. The material of choice was Orgasol polyamide- a natural polyamide 12 powder possessing the physical and chemical properties suitable for this application. The specific additive manufacturing process to be used was determined to be Selective Laser Sintering, and a printer capable of performing the same was identified as Formlabs Fuse 1. The aforementioned printability analyses were carried out in accordance with these considerations and the model was found to be well in order for the same.

IP validation has become more challenging for FPGA device as it supports high operating speed. PCIe is an IP used for high-speed data transfer. The link training and Initialization takes place at physical layer to initialize the link width and link data rate. The physical layer is getting more complex when it supports higher speed. The stability of link training is improved by optimizing the soft logic design in application layer. Two protocol tests usually validated in industry are link up testing and link & higher layer testing. Debugging tools supported by Quartus are fully utilized to detect any failure during link training. The characterization of link performance covers process corners, voltage and temperature conditions are hard to analyse. The H0 statement shows a significant difference for passing and failing case. The p-value is greater than 0.05 proved H0 statement is accepted. The difference on passing and failing percentage is insignificantly impacting overall link performance of PCIe. It concludes that the bug is random and not caused by any defects on the silicon layout of FPGA device. Thus, IP validation shows the robustness of the device and able to comply with base specification of PCIe.

This project aims to design a notifier of a cultivation room used to cultivate king oyster mushrooms (P. eryngii spp.) using an SHT75 temperature and humidity sensor. When the temperature or humidity of the cultivation room is beyond the mushrooms' growing condition, the notifier will notify the cultivator by showing the texts to let the cultivator be conscious of the surrounding temperature and relative humidity. In this project, 8051 microcontrollers simulator (EdSim51) used to design the notifier. The component used to imitate the function is the SHT75 sensor, Liquid Crystal Display (LCD) module, Light Emitting Diode (LED) bank and Universal Asynchronous Transmitter (UART-Tx). Temperature and humidity parameter classed into low, normal, fruiting, high and over-limit condition. The system developed was successfully detected all the parameter. The notifier designed can solve the problems faced by most cultivators in cultivating mushrooms and helps to grow other plants in the future.

The programmed water system frameworks are received as of late to provide support to the agriculturists in turn reducing the manpower and improving cost effective techniques. In this paper, a detailed survey is done analysing the crop detection techniques which are in existence. This paper provides an insight study on pH level monitoring in the soil, water and soil nutrients management techniques, temperature and humidity measurement, surveillance of crop field and other smart irrigation techniques utilized for monitoring the farmland. This paper discusses about the effective methodology with enhanced technique that could be implemented in future to attain better performance and user-friendly for the farmers.

The main cause for land pollution is overflow of garbage. It makes insanitary condition for the encompassing individuals and cause ailment. This paper focuses on the review of various existing techniques available for garbage monitoring. In this article, survey about the waste monitoring methods, garbage disposal techniques and technologies utilized for developing a system to deal with waste management are presented. Finally, an efficient system is proposed along with waste disposal method that can be used in future for achieving better performance and cost effectiveness.

In order to ensure the remaining volume of liquid inside a tank that is normally checked manually and frequently, an unmanned monitoring system is proposed. The proposed system is developed based on the concept of Internet of Things (IoT). This paper presents a prototype for tank level monitoring. The prototype utilises SRF HC-SR04 sensor to measure the liquid level. Arduino Uno microcontroller is implemented to assist the data processing before any notification is sent to the user. The remaining liquid volume and LED notification are shown as the output of the prototype. Some testing have been conducted to observe if the prototype works fine and to measure any error during implementation. Result shows that the relative error is less than 2% and the standard deviation is less than 5%.

An Intelligent Shophouse System has been developed and built which can applied in most of the small-scale stores such as convenient store and retail pharmacy. By implementing IoT, efficient customer monitoring systems enables to limit the customers from enter to the store and practice hygiene environment within the store. Compromising of different sensors which capable to detect the customers that come into the stores and track for the number of customers inside the store. The information from sensor help to count on for the customers and display the available spaces at outside the premise. An ESP32 is used to allow bidirectional communication between sensors and MIT application. The data from sensors will always updated into the IoT Cloud and users able to view the number of customers inside the premise in real time, while the users able to adjust the limitation of customers at anytime. Contactless hand sanitizer implemented to ensure hygienic of the customers and reduce spreading of virus. This is beneficial for users especially for shop owners which would like to limit and monitor number of the customer inside the store without being in contact with them and help to reduce the virus in their surroundings.

Due to depletion of fossil fuels and increasing power demand, employing Renewable Energy Sources (RES) in the form of micro-grid has become very essential. However, the reliable operation and control relies on the intermittent nature of RES and maintaining the frequency within the acceptable limit is the challenging task in isolated micro-grid. This paper presents the Automatic Load Frequency Control (ALFC) in an isolated Micro-Grid (MG) with Superconducting Magnetic Energy Storage (SMES) unit using Integral controller, to enhance the stability of the system frequency. The simulation result shows that the dynamic performance of the proposed system is significantly improved while incorporating the SMES Unit. The simulations are carried out in MATLAB – Simulink.

Crop cultivation has been around for a long time and plays essential roles in many fields. Growing plants' growth quickly affects climate conditions, especially temperature and relative humidity. Therefore, the simple Green House Management System designed using an SHT75 sensor to detect the temperature and relative humidity inside the greenhouse. The temperature and relative humidity calculated in the form of degree Celcius and percentage. The data then displayed on the LCD monitor. The water pump activated if the temperature and relative humidity are larger than 35°C or below 45%. If the relative humidity is above 45%, the ventilation fan is activated. The user can also use the PC keyboard connected to the activated water pump or ventilation fan. This report explains the design process while highlighting the problems faced by the farmer. Lastly, the conclusion of this project based on the objective and the results obtained. Besides, some suggestions discussed based on the design for the future development of the system.

The husbandry is very important business of Indian farmer. Dairies collect milk from farmer everyday & payments for this milk are done according to the quantity and quality of milk. This rate depends on various quality parameters of the milk. Fat is one of most important component of milk. Due to its higher importance along other quality parameters of milk, it becomes mandatory for the determination of fat percentage especially for the milk vendors, small dairy owners etc. The classical method used to determine the fat percentage in milk is Gerber method. It's a chemical test which is destructive in nature. Due to inclusions of various chemicals it becomes time consuming procedure for determination of fat in milk. Due to this, the number of samples that can be tested is very low in a given period of time. This paper presents the design and development of Milk Fat Analyser. The system is built by interfacing Light Dependent Resistor (LDR) with Raspberry pi Microprocessor. The parameter that is measured is fat percentage. The result obtained is displayed on screen which provides a good interface to the user. This project aims to provide a low cost, fairly accurate and reliable system to the farmers, small dairy shop owners and similar small factories where quality of milk matters while processing it to make other milk products and also for supplying milk consumed by people at large. Experimental results show that the method with Machine learning algorithm can detect fat with fair accuracy.

In this paper, a new safety method is proposed to reduce the pressure cooker risks, accidents due to the carelessness of the user. The main aim of the paper is to introduce a gadget that can be used to keep track of the whistle count and notify the user in real-time about the whistle count through their mobile phones. This way the user can keep track of the whistle count and can turn off the pressure cooker when their desired whistle count is reached. Sound sensors are used to detect the sound wave of the pressure cooker whistle. The whistle count is recorded using an Arduino and the notification is sent to the user's mobile via the Blynk application. Blynk is being the open-source platform for a modular graphical user interface to control experimental tools based on Arduino, it extends Arduino's capabilities allowing instrument makers to easily create a custom user interface program that runs on a connected computer. This device can be used in an indoor environment.

Vehicular Ad-hoc Networks is a interesting and key research area which have more number of issues which needs immediate attention when moving towards intelligent transportation system. In this research work, we have proposed a new mechanism of IP scheme which highly helps in handover of vehicle from one RSU to RSU. RSU is playing a key role in delivering of one vehicle from its range to other RSU. Here, how Quality of service can be handled when unexpected handover happens between RSU. So, A new mechanism to predict the vehicles which may enter into handoff process based on its mobility and GPS location. This proposed IP scheme and the predicted handoff is tested through two protocols called Weighted Clustering algorithm and also with Mutated K-Means algorithm to test the performance. The results shows better results to maintain the QoS demands of the vehicle when the handoff is predicted in prior.

The late 2019 outbreak of Coronavirus Disease (COVID-19) had an indelible imprint on the humanity. The world is recovering from the outbreak but there is danger of a second wave of the outbreak. To get rid of the outbreak it is necessary to prevent the viral transmission and it is need of the hour to maintain social distancing and wear masks in public areas. The governments are providing strict guidelines to wear masks in public places. It is not manually feasible to check if people are wearing masks or not. In this paper, process of detecting face masks in public places is automated using Convolutional Neural Networks by performing comparative analysis on Sequential bi-layered CNN, VGG-16 CNN and MobileNetV2 CNN architectures. Among these three architectures MobileNetV2 outperformed with a performance accuracy of 99.2%. The efficient Deep Learning architecture of detecting face masks can be achieved with the help of IoT (Internet of Things) devices and cameras, of those who are not following guidelines in public places. Such a system is very useful in post outbreak period and can be installed in public places such as Railway Stations, Airports, Parks, Schools, colleges, offices etc. to track and ensure wearing of masks by people. The contribution of this paper is not to reel-off the finding from the original paper on Face Mask detection with various architectures rather to provide results on the efficiency of using the MobileNetV2 architecture in comparison with Sequential CNN and VGG-16 architectures for crowd analysis mask detection.

Deep Learning is considered one of the most effective strategies used by hedge funds to maximize profits. But Deep Neural Networks (DNN) lack theoretical analysis of memory exploitation. Some traditional time series methods such as Auto-Regressive Integrated Moving Average (ARIMA) and Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) work only when the entire series is pre-processed or when the whole data is available. Thus, it fails in a live trading system. So, there is a great need to develop techniques that give more accurate stock/index predictions. This study has exploited fractional-order derivatives' memory property in the backpropagation of LSTM for stock predictions. As the history of previous stock prices plays a significant role in deciding the future price, fractional-order derivatives carry the past information along with itself. So, the use of Fractional-order derivatives with neural networks for this time series prediction is meaningful and helpful.

The 4^th Industrial Revolution (Industry 4.0) necessitates implementing the prognostics and health management (PHM) practices in manufacturing processes. The traditional machine learning approach has well assisted the PHM practices within the same data distributions. However, when a high noise environment, versatile operating conditions, and cross-domain machining is considered, it still lacks key steps of generalizing unknown tool faults. In an attempt to address PHM practices under such domains, a generic Deep Learning-based scheme is gaining significant attention. In this paper, an inclusive review is presented in order to provide an insight into the application of DL in tool condition monitoring (TCM), particularly in milling. Commonly used DL algorithms and their applications toward TCM are initially discussed and number of illustrative DL models applied for TCM is presented. Later, emergent DL themes & their computational techniques are summarized with an intention to provide framework for domain generalization. Finally, challenges in further exploration and futuristic trends in TCM are discussed.

The Internet of Things (IoT) has upgraded the things and regular devices around to smart devices that can interact, share information and collaborate. With the plethora of IoT products, solutions, and workflows available online, the consumer finds it challenging to find the most suitable one. IoT, when integrated with the recommender system, can extend its features to the new space of innovation, usability, viability, and success. Various recommendation techniques can be employed to support users to get the best fit services, applications, sensors, products, and IoT workflows. This article will steer via the basic introduction of the IoT, its building blocks, hardware, software, applications, and its challenges. It analysed scientific articles indexed in the Scopus database with help of biblioshiny tool based on Rstudio software. The analysis is directed on 260 articles to figure out the trending amalgamation of Recommender System with the Internet of Things. Results point to fact that personalized recommendations for IoT-based applications are the most worked on topic by the authors.

Tourism is one of the fastest growing business domains. Self-assisted services and Internet of things-based devices have become the current age cash. Internet of Things is a network for devices to connect and communicate information using physical devices embedded with sensor, software, cloud computing and other technologies. Therefore, self-assistance options enhance customer experience when it comes to hotel accommodation. The Internet of Things plays major role in improving the stay experience by providing customized services to customers. Self-services like pre-booking, registration and user preferred payment mode, automated check in & check out are also few aspects that are contributing for improved guest experience. In this paper, role of Internet of Things in hotel industry is taken into consideration for improving the guest experience and providing the customized services and the application of IoT in hotel industry has been analyzed.

WSN is a network comprising of various sensor nodes that are highly energy efficient used in various applications now a days. It helps in transmitting data from sensor nodes to the base stations in a highly reliable and secured manner. It plays a very important role in real world and integrates with many other technologies like Cloud Computing, Internet of Things (IoT). Different researchers continuously attempted to work on different constraints under Wireless Sensor Network which further becomes research motivation. In this paper, we highlighted various issues facing by different researchers while data transmission among sensor nodes. WSNs are used in various areas in all over the world, and significant progress has been made to expand the use of sensor nodes over the past two decades.

Cloud computing is a technique to minimize the use of hardware and software infrastructure digitally for the dynamic delivery of services. There are numerous components of current cloud computing models: end-user computers, networks of contacts, access management systems, and infrastructures of applications. Different organizations of cloud computing are providing various policies for handling tasks of cloud vendors and consumers. During task migration, whenever data is transferred over the cloud from one node to another; then the sink node should be trustworthy. It becomes a challenging task to create reliable and trustworthy cloud platforms. As the base from the concept of cloud computing, many authors proposed data privacy, security problems, security challenges, trust models, trust issues, challenges of trust management In this paper, we highlight some of the trust issues faced by both cloud vendors and cloud customers while using cloud services.

Handwritten Signatures are special types of behavioural biometric which are used in many applications such as banks, credit cards, passport, check processing, and financial documentation, etc. Verification of these signatures is a challenging task especially in the case of offline where there is no information of signing process. So there is a need for a system that can distinguish between the genuine and the forged signature to avoid the chances of theft or fraud. Many types of researches have been done in this area in the last three decades. Earlier this task was performed by handcrafted features and recently deep learning techniques have been employed for this task, but still, there is a chance of enhancement in the accuracy of the system. In this paper, we present a comprehensive study of the work done in the field of offline signature verification and also the challenges which are still present in this area.

Internet of Things (IoT) is an advancing technology that is a network of many smart devices connected together to provide services to various application domains such as smart offices, health monitoring, agriculture, etc. IoT-based recommendation technologies are becoming one of the key requirements that will recommend future IoT solutions. A review of existing recommendation technologies in the vibrant field of IoT is discussed in this paper. The main aim of this paper is to present a comprehensive analysis of existing literature on recommendation approaches. Several issues of applying recommendation systems to IoT are also discussed. Nearly 1000 research papers have been considered for analyses which are published by ACM, Springer, IEEE and Science Direct from 2011 to 2017. Finally, the recent research trends are spotted for future researchers intended to work in the recommendation-based IoT domain. Moreover, this paper also envisages the future of the Recommender System (RS) that opens up the newest research directions for young researchers.

Since the advent of start-ups and old companies starting to shift to e-business, it has become troublesome to choose the right methods for projects that's where extreme programming came to use. In this paper, we tried to compile different applications of the same. Extreme programming is a well-known agile method for software development. Extreme programming ensures customer satisfaction, better software quality and efficient project management. The team size is usually small but the group is team-oriented. It is a dynamic software development model, i.e., continuous discussion and integration of new features and ideas is the cornerstone of this model.

Resource allocation in cloud computing is inherently a challenging task due to the increase in the number of cloud users working on multifarious cloud applications in some of the infrastructure. The majority of resource allocation techniques existing till have focus on providing performance driven by the workload of the applications from diverse domains like scientific and business. This paper presents a detailed review of meta-heuristics algorithms for resource allocation in cloud computing environment. The reviewed meta-heuristic algorithms are capable of achieving much higher performance, reduction in a cost, reduction in time, improve utilization of resources, improve energy efficiency while resource allocation in cloud.

Tool wear may depreciate the quality of the machined product owing to its poor surface roughness and dimensional inaccuracy. Tool condition monitoring system (TCMs) is necessary for the manufacturing industry to obtain better quality products with minimal time and improve productivity. Currently, TCMs uses different sensor signals and features to examine the tool wear. In this work, an Integrated kurtosis-based algorithm for Z-filter (I-Kaz) 2D and 3D analysis is employed to examine the vibration signals in milling of Inconel 625 for monitoring the tool condition during the milling process. The results from vibration signals revealed that the I-Kaz coefficient correlates with flank wear. I-Kaz coefficient was increased for raise in flank wear. When the I-Kaz 2D coefficient value increased above 0.5, it indicates that the tool was worn out and has to be replaced.

Every industry is now turning towards industry 4.0. In this era, industry requires smart machine tools. But for small scale and medium scale industries, it is not affordable to buy new smart machineries. Therefore, the fault diagnosis system (FDS) has got unavoidable propensity in the machine of modern huge information and smart manufacturing. Simultaneously, it offers a solid answer for taking care of the mechanical machines & its cutting tools health status. Industry 4.0 and its key advances assume a fundamental part to make mechanical systems independent and along these lines make conceivable the automated data assortment from modern machines/cutting tools. In view of the gathered information, ML algorithms can be applied for automated shortcoming identification and finding. It is difficult to choose relevant machine learning (ML) procedures, kind of data, data size, and hardware to apply ML in mechanical systems. Determination of wrong FDS procedure, dataset, and data size may cause increase in downtime and infeasible for scheduled maintenance. Accordingly, this study aims to present, the brief review of literatures for investigation to find existing methodologies of ML and its applications, Supportability to develop novel system to diagnose faults in CNC hobbing cutter and to choose suitable ML methods for their required FDS.

In the modern days, use of vehicles is increasing rapidly. It is very essential that the vehicle must have a good control mechanism which ensures the safety of the vehicle. The brake system in automobile is one of the important control element which needs to be monitored. The unconditional brake leads to catastrophic failures. Hence, the brake system should be monitored regularly. An experimental study is proposed for the brake system monitoring using vibration signals. The vibration signals are captured under all possible brake conditions. The hidden information in the vibration are extracted as statistical features. We carry out the feature selection. Classification using the selected features is the final step in machine learning (ML). Meta family classifiers are used for the study. Among the considered classifiers, Bagging algorithm produced 80.8 % accuracy for monitoring the brake condition.

Friction stir welding (FSW) is a relatively new solid-state joining process. This joining technique is energy efficient, environment friendly, and versatile. In particular, it can be used to join high-strength aerospace aluminum alloys and other metallic alloys that are hard to weld by conventional fusion welding. FSW is considered to be the most significant development in metal joining in a decade. Recently, friction stir processing (FSP) was developed for micro structural modification of metallic materials. In this review article, the current state of understanding and development of the FSW and FSP tool process parameters are addressed. To identify the tool parameters, it is necessary to monitor the tool condition. Diagnosis the recognition of the nature and cause of a certain phenomenon. It is generally used to determine cause and effect of a problem. Machine fault diagnosis, a field of finding faults arising in machines. To identify the most probable faults leading to failure, many methods are used for data collection, including vibration monitoring, Thermal imaging, Oil particle analysis etc. Then these data's are processed using methods like spectral analysis, wavelet analysis, wavelet transform, Short term fourier transform, high resolution spectral analysis, waveform analysis etc. The results of this analysis are used in a root cause failure analysis in order to determine the original cause of the fault. This paper presents a brief review about one such application known as machine learning for the friction stir welding tool monitoring.

The advent of industrial automation has brought about a substantial change in the human lifestyle and the way human interaction with machines. One of the major technological interventions in day-to-day life is the role of automation, which has uplifted the living standards in developed countries and fostered humans' dependency for accomplishing recurring tasks. The latest and most adopted technology for remotely monitoring and controlling any machine or device is the Internet of Things-which has become one of the industry standards for automation. Multiple edge computation capable embedded devices and machines are connected to the internet as independent nodes, which can be monitored and controlled remotely with the use of IoT. Adapting this cutting-edge technology for household appliances to monitor and control them is often seen nowadays. This is fast and reliable but arrives with its own snags such as availability of internet at place where user and also the device/appliance is located, use of single control strategy which hampers and restricts the user always to carry the remote or to stay in the vicinity of the device to be controlled in case of wifi or Bluetooth controlled automation. The proposed research focuses on the adoption of multiple strategies to control each device/appliance to empower the end-user without being restricted to depend on a single strategy remote controlling system. The core part of the proposed research revolves around the Message Queuing Telemetry Transport (MQTT) protocol but can be activated with multiple routes such as touch-based sensing panels, cellphone-based controlling, web-enabled controlling or even gesture-based controlling of the appliances resulting in an ameliorative user experience and interactions with machines.

An organic LED (Light emitting diode) farming using artificial intelligence is the way to increase crop production effectively with LED lights. Users can able to select specific range of wavelength to induce targeted photomorphogenic, bio chemical, or physiological plant responses. LED can prevent physiological disorder that are commonly existing in indoor environments, and helps in reducing if pest and diseases pressure in growing plants.

There are various situations where face shields and mask play an important role such as for doctors in operation theatres, healthcare workers diagnosing/treating patients with infectious disease, traffic police and construction workers working in environments with high levels of dust and air pollution, welders working at high temperatures, bike, bicycle riders and many others. A face shield-cum-mask can be useful to protect from infectious bacteria, virus, parasites, debris, hazardous chemicals, sparks etc. Knowing the potential need and importance of face shield and mask, its usability can be further enhanced by operating them based on sensors. We have built a prototype of 3D printed visor attached with face shield-cum-mask integrated with proximity sensors, battery and circuitry which is used to move the visor above or in front of the face as and when required by movement of hand close to the sensor.

The incubator is an apparatus that is used to regulate environmental conditions such as temperature, humidity control in an enclosure. To maintain the temperature of the incubator is difficult and challenging. This research paper proposes the design of an incubator temperature control by using fuzzy based PID. The proposed model construct of two fuzzy logic based PID controllers to control the temperature. This paper principally focuses on the designing of new fuzzy self-tuning PID algorithm. The error and changing error rate are inputs of the fuzzy based PID controller. The PID parameters are outputs of the fuzzy based PID controller. A set of fuzzy rules is used to regulate the PID parameters. The simulation result shows that the rising time, settling time & overshoot had reduced compared to PID control.

The world is enduring difficulties in numerous fields because of this Coronavirus pandemic flare-up. All government had played it safe to forestall the infection transmission, for example, rehearsing social distancing and temperature checking before entering any preface just as declaring a lockdown. Notwithstanding, the 1-meter distance is not straightforward to estimate by unaided eyes, and it is difficult to carry along a meter rule regularly. Subsequently, inadvertently connect with others. Therefore, this would build our danger of getting contaminated by the COVID-19 infection. Moreover, the thermometer put at each person's passageway has the threat of causing disease since numerous individuals share it. Regardless of whether a specialist is appointed to quantify guests' temperature, the person does not have the option to keep up the guest's social distance when taking temperature. In this research, a sensing bracelet proposed to determine physical distancing and temperature. The bracelet has two fundamental capacities. It can continually screen distance among client and others utilising a sensor. It will warn the client to keep up social distancing and avoid swarmed places when it distinguishes individuals under 1 meter. Second, it has a temperature sensor to determine the client's internal heat level and will ring to caution the client if the internal heat level is more than 37.5°C. The experiment conducted able to achieve the requirement for a physical distancing.

Technology is so ahead that sophisticated processes could be accessed and controlled by a smart phone through which human-machine interaction is made easy and taken to the next higher level. A classic example of a highly unstable non-linear mechatronic process is a ball-plate balancing system. This paper presents the mathematical model and design of a typical two axes ball-plate balancing system, where the roll and pitch of the plate is controlled by the actuation of two servo motors. An image processing algorithm acts on the video feed obtained by a vision system, to read the position of the ball on the plate in real time. A proportional-integral-derivative controller is implemented to position the ball on a desired location on the plate. A mobile application forming an intuitive human-machine interface is developed to interact, monitor and control the operation of the ball-plate balancing system. The developed system has an error of 1.29 % in positioning the ball with a settling time of about 26.4 seconds.

Farming is a labour intensive occupation and there is heavy shortage of agricultural labours due to rapid urbanization. In India agriculture contributes about 15% of the gross domestic product and there is need for mechanizing the agricultural activities to meet the raising demand for food and labour shortage. In this regard, a guided all-terrain vehicle will be designed and developed in this study to help the farm labour in his regular agricultural activities. The all-terrain vehicle has capability to traverse through rough terrains and it will be IoT(Internet of Things) enabled so that it can communicate with the various subsystems in the cloud and can be also monitored and controlled remotely. The vehicle will be guided and controlled by human through a proper interface. It will be designed with farming specific accessories hence it would reduce human efforts during his farming activities. Thus the proposed vehicle will act as farmer's friend in assisting him to perform his tasks and thereby increasing his productivity.

This research paper focuses on the new method of a retrofittable Adaptive Headlight Control System (AHS) for automobiles like car, trucks, etc., Adaptive headlight system is the technology where the headlights can adjust their illuminating radius with respect to the steering angle and able to self-level its position depending upon the terrain and intensity of light beam changes dynamically high or low according to the oncoming vehicle. This system also considers the benefit of other motorists on the road. In the existing system, mechanical links are incorporated with the front lighting system and steering wheel, and the angle of light will change according to the requirements and the cost of this system is high which is mostly used in higher-end vehicles. In this study an attempt is made to develop a adaptive headlight system which can be retrofitted in an existing model of an automobile providing improved illuminating angles and light visibility under various terrain and road conditions. The proposed AHS system could be useful for applications like different lighting beams (low, high) and also for levelling operations. This system could be a better replacement for conventional headlights seen in low, mid-end cars and would help in the prevention of accidents especially during night driving.

Coordinated adaptive cruise control (CACC) is a type of adaptive cruise control (ACC) that enables the driver to set the vehicle speed and the distance between current and preceding vehicles as well as helps to gather the data from vehicles around it and form a platoon. The main objectives for the paper are to implement coordinated cruise control, to minimize steady state spacing error while maintaining the string stability and to get earlier settling of string stability under external disturbances. Design, simulation, and testing of CACC under various conditions have been performed. Both feedback and feed forward controls have been employed for implementing the system model with controllers. It is assumed that all vehicles are having wireless access to share the speed and distance related information. It is observed that settling time for the string stability has been improved. The model has been simulated under disturbances and results are compared with existing ACC control. The simulation results validate proposed model in terms of settling of string stability.

This paper deals with the optimization of LCC Resonant Converter based on Differential Evolution Algorithm. Closed Loop Analysis of LCC Resonant Converter have been Simulated by tuning PID Controller for different values of Kp, Ki and Kd values. Optimum Values of Kp, Ki and Kd were obtained using Differential Evolution Algorithm and these values were fitted to Obtain Maximum Output Voltage with LCC Resonant Converter. Initially three Variables namely Series Inductance, Series Capacitance and Parallel Capacitance were considered, out of which the Value of Series Capacitance was tuned with Differential Evolution.

When the regulations were first formulated in 2008, one of the potential way's automakers were supposed to meet the goal of 95g CO2/km by 2020/21 was the hybridization of vehicles. Market participants and customers are becoming more interested in electric vehicles. Infrastructure, high-power device complexity, driving distance and requirements for protection all seem to be obstacles that will take longer than anticipated to integrate, followed by fuel cell vehicles, which will be the new significant thing, particularly in the commercial vehicle segment. As an outcome, hybrid vehicles with 48V architecture are perceived as the forerunners of complete electrification. It outperforms traditional in terms of fuel efficiency and high voltage hybrids in terms of price and time-to-market. Evaluating a control approach for torque management between the motor and engine and mode change decision, namely, from electric to the hybrid mode or likewise, is a major challenge for automotive service providers for hybrid electric cars. Each of these dynamics will directly affect fuel efficiency and manoeuvrability, notably during mode transition. Research work presented and examines a new idea for improved driving dynamics on a P3 mild gasoline car in Modified Indian Driving Cycle (MIDC) 1^ST stage (urban) under system constraints such as sustaining 12V battery voltage, lower battery 48V SOC, and so on. The novel method that has been implemented is focused on two techniques. I. A modified Adaptive Equivalent fuel consumption minimization strategy for the engine's and the motor's power distribution, and II) A rules-based mode change decision.

The growing use of brake systems in enhancing vehicle performance along with safety has promised a greater class of innovation. The presented research first discusses a vehicle dynamics model that accounts for the longitudinal and lateral forces acting on the wheels to compute the yaw moment acting on the vehicle based on the steering angle. Dynamic load transfer due to combined action of gravitational load, gyroscopic couple and centripetal force for real-time behavior is considered in the vehicle dynamics model. With a difference in theory and practice, work then focuses on the various disturbances that affect the dynamics of any vehicle under yawing action. The effect of wind disturbance is considered in-depth for the research and other factors like undesirable tire behavior have been discussed as well. For yaw moment compensation, a unique brake system layout with two circuits (primary & secondary), making the use of shuttle valves has been devised and a closed-loop control system is implemented. Each wheel is autonomously provided a brake force by an electromechanical actuator, computed by its respective PID controller to compensate for the variation in yaw moment caused due to external disturbances.

Conductive inks have been extensively researched owing to their popularity in Printed Electronics and Flexible Electronics. IME is one of the most important technological developments of this century. In an effort to summarize the latest advancements created by Injection Molding, Thermoforming and Printed Electronics in the field of In-Mold Electronics, this consolidated report describes the key technologies and challenges in meeting the requirement of Automotive Cockpit Electronics and its specifications, as well as an overview of Touch Capacitive sensors development with a range of conductive inks and techniques.

Brain computer interface wheel chair specially designed for paralyzed and disabled person who are not capable to operate normal wheel chair. This wheel chair is based on (BCI) Brain computer interface, it can control the wheel chair from brain neurons by the help of BCI. Brain computer interface (BCI) is a computer-based system that obtain brain signal that can be controlled by Neurosky Sensor which is an electrophysiological process to archive the electrical activity of the brain. A BCI system recognize users to grant their determination by study their brain signals. This technology is very helpful for paralyzed and disabled person they can easily moves wheel chair in any direction.

Cardiac Pacemakers have been effectively implemented to balance the electrical conduction network of the heart; A pacemaker's primary function is to control an optimal heart rhythm, either because the elementary design of pacemaker of the heart is not quick enough, or because there is a barrier in the electrical conduction mechanism of the heart. Modern pacemakers are capable of external tuning and it enables optimal pacing modes for individual patients to be selected by a cardiologist, especially a cardiac electrophysiologist. In this study, linear and non-linear control logic for the regulation of the electrical response from the cardiac pacemaker has been studied with evaluation. The logic is constructed based on the mathematical model of the heart which has been converted from physiological model to electromechanical model. The pacemaker regulation, based on the control logic is evaluated on the grounds of the PQRST wave complex and the precision of the complex.

The focus of this work is to develop a new safety system in addition to reduce accidents for innocents in automobiles. When confronted with an accident, the only safety measure which we bet our lives on is "airbags". In several cases, airbags alone may not be able to completely protect the passengers in the vehicle due to the high magnitude of the impact. In the present work, a new safety upgrade will be modeled in vehicles to absorb the sudden frontal impacts while in motion. The ultrasonic sensors are placed in the front portion of the vehicle which is set to propagate and receive ultrasonic waves while moving. The change of distance from the sensor to the obstacle is monitored continuously and in the event of an emergency, the frontal safety system in the vehicle gets activated. In such an event, the bumper or a metallic formed plate is actuated forward to a certain distance and upon striking the obstacle, the impact force is then reduced by shock absorbers or springs provided in the safety system. Hence, the impact transmitted to the passengers inside the vehicle is less when compared to the direct impact.