The Internet of Things (IoT) is a continuing massive excitement for machine-to-machine communications to encourage individual devices to use the internet for data sharing. This work introduces the design and performance of continuous transformer monitoring and failure diagnostic and documents main distribution transformers indicators such as load current, transformer oil level, gas formation, and temperature. By using this project one must continuously take a look at it and it will reduce progress and maximize the stability, accuracy, and performance of this project. The sensors are used to track recurrent errors or voltage intake variations. The observed information is transmitted to the microcontroller and it tests parameter limitations that send it to the IoT web server using the IoT module. This data sharing means that the appropriate data are presented to the customer and before any significant errors occur according to the collected data the user will make useful choices.

The most popular method for transporting fluids, and gases is through pipelines. For them to work correctly, regular inspection is necessary. Humans must enter potentially dangerous environments to inspect pipelines. As a result, pipeline robots came into existence. These robots aid in pipeline inspection, protecting numerous people from harm. Despite numerous improvements, pipeline robots still have several limitations. This paper presents the design and motion planning of a wheeled type pipeline inspection robot that can inspect pipelines having an inner diameter between 250 mm to 350 mm. The traditional wheeled robot design has three wheels fixed symmetrically at a 120° angle apart from each other. When maneuvering through a curved pipeline, this robot encounters motion singularity. The proposed robot fixes the wheels at different angles to address this issue, allowing the robot to stay in constant contact with the pipe's surface. Motion analysis is done for the proposed and existing robot design to study their behavior inside the pipeline. The result shows that the proposed robot avoids motion singularity and improves mobility inside pipelines. 3d printing technology aids in the development of the proposed robot. The experimental tests on the developed robot inside a 300 mm-diameter straight and curved pipeline show that the robot avoids motion singularity.

The focus of this work is to investigate the adhesion characteristics of a permanent magnet arrangement over ferromagnetic surfaces for wall climbing robot applications. The changes in wall thickness affect the adhesion characteristics of the robot, this in turn influences the payload and alters the operating conditions. The effect of varying the wall thickness on the adhesion strength of a wall-climbing robot is an area barely investigated and this is being explored in this work. A two-dimensional model of the adhesion mechanism and the ferromagnetic surface is developed and simulated in this study. The adhesion characteristics are studied for different thicknesses of the ferromagnetic surface with different grades of the magnet. Two different standoff distances which comprise the gap between the magnet and the surface to be inspected are investigated therein. Experimental studies are also carried out to measure the performance, and the results show a strong correlation with the simulation results. Simulation with experimental validation of magnetic adhesion presented will provide better insights into magnetic wall climbing systems.

Over the past decades, developments and scientific breakthroughs in the field of robotics have shown the replacement of wheeled robots with legged robots, which are often inspired by the biological characteristics of legged animals. Many industries and urban-based applications promote quadruped robots because of their dexterous ability to efficiently handle multiple tasks in the working environment. Motivated from the recent works in the field of quadruped robots, this research aims to develop and investigate gaits for a 2 DoF mammal-inspired quadruped robot that incorporates 4 hip and 4 knee servo motors as its locomotion element. Forward and inverse kinematic techniques are used to determine the joint angle required for the locomotion and stability calculation are presented to determine the center of mass/center of gravity of the robot. Three types of gaits such as walk, trot, and pace are developed while keeping the center of mass inside the support polygon using a closed-loop control system. To minimize errors and improve the performance of the robot due to its non-linearity, a meta-heuristic algorithm has been developed and addressed in this work. The fitness function is derived based on the Euclidean distance between the target and robot’s current position and kinematic equations are used to obtain the relation between joints and coordinates. Based on the literature, particle swarm optimization (PSO) was found to be a promising algorithm for this problem and is developed using Python’s ‘Pyswarms’ package. Experimental studies are carried out quantitatively to determine the convergence characteristics of the control algorithm and to investigate the distance traveled by the robot for different target positions and gaits. Comparison between experimental and theoretical results prove the efficiency of the proposed algorithm and stability of the robot during various gait movements.

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