This dissertation aims to reuse the cold water which will initially present inside the water heater and reduce its wastage by sending it back to the water tank. The water heater temperature could be customized based on the number of users either manually or in an automated way using Internet of Things (IoT) techniques. The system is designed and operated using open‐source hardware and an IoT platform. The smart solar water heater with IoT capabilities continuously monitors the tank level, temperature, and pH level, and the data collected by the IoT node is uploaded/published to ThingSpeak. The IoT cloud analyses the sensor value and instructs the control unit of the smart solar system. The IoT enabled solar water heating system efficiency is high for smart homes and Industry 4.0. The main advantages of this model include handling multiple users, reducing the wastage of cold water, and purifying the water based on TDS level and this model aims to make it possible to control the proposed system from anywhere and at any time. The highest efficiency of the respective solar water heater could be well utilized.

The issue of the energy shortage is affecting the entire planet. This is occurring because of massive population and industry growth around the world. As a result, the entire world is attempting to implement green networking systems and manufacture the power/energy efficient products. This research work discusses the green networking system technologies. This work introduces a power‐efficient control unit (CU) design and implemented on the Zynq SoC (System on Chip) ultrascale field programmable gate array (FPGA). The VIVADO HLx Design Suite is used to simulate and analyze the CU model which is considered as one of the key components of central processing unit (CPU), used for data communication purposes. The CU is made suitable for the green communication by making it power‐efficient. Therefore, the power consumption of the CU is analyzed for the various set frequency value ranging between 100 MHz and 5 GHz, and it is discovered that as the clock frequency rises up, the total power consumption also tends to get increased. The total power of the proposed model is reduced by 77.42%, 21.29%, and 17.93% from three models, respectively, being compared in the present paper. Final results shows that the CU is better suited to run at low frequencies to optimize power consumption.

This research presents a vehicle ID‐based congestion aware message (CAM) for beacon signals on the vehicle environment. At the MAC protocol of the vehicle environment, enhanced vehicle ID‐based analysis model is given first. With the automobile ID embedded in their separate CAMs, the model weights the randomized back‐off numbers chosen by cars engaging in the back‐off procedure. This leads to identifying a car ID‐based randomized back‐off code, which reduces the likelihood of a collision due to the identical back‐off number. A traffic density based‐congestion control algorithm (TDCCA) is suggested in this research. The revised mathematical approach surpasses previous work’s overall packet latency because just one‐fourth of the congestion window is employed during the experiment. The research includes a congestion management method that adjusts the rate of CAM transmitted over the host controller to improve the efficiency of the model parameters. The method considers various circumstances, from nonsaturated to substantially saturated networks (in terms of congestion probability) and sparsely dispersed and teemed networks (in the form of vehicular intensity). The technique is run across various automobile ID‐based back‐off values for high‐standard results analysis. The simulation outcomes in terms of packet delivery ratio, energy consumption, delay, success rate, and collision ensure the effectiveness of the TDCCA method. Even at high traffic densities, the automobile ID‐based CAM following information method outperforms the typical fixed CAM frequency IEEE 802.11p, according to simulation findings for all back‐off figures.

In recent decades, there has been a growing interest in the design and development of power loss reduction in electric drive systems. To realize the full potential of the Brushless DC motor (BLDCM), the design methodology of an effective intelligent controller is vital. On the other hand, the Landsman converter is used in a bridgeless configuration to enhance the power factor and minimize the power loss of the BLDCM. In addition, BLDCM utilizes the different intelligent controllers that are used to decrease power loss. The performance of the Landsman converter and CSC converter is analyzed concerning various configurations/stages, and the numerical MATLAB 2016a simulation results are discussed to arrive at the suitable intelligent controller for the BLDC motor, and comparison results are presented. The proposed converter is designed and validated using hardware implementation by minimizing power loss. Effectiveness can be tested and valued for the proposed controller for the various intelligent controllers of BLDCM.

A huge unexpected upheaval, a blast, or the emanation of any lethal gas because of mishaps, inadequacy or simple carelessness by industry authorities, has brought about innumerable passing’s, wounds and caused huge harms, upsetting the lives of the sufferers' as well as the ages to come. To stay away from any potential debacle of this greatness, this task proposes a modern checking framework dependent on the Internet of Things (IoT). This structure venture makes a mechanical observing framework that identifies abnormal measures of gases, for example, carbon monoxide, LPG, butane, hydrogen which could cause a blast. It additionally screens the dimensions of air contamination ousted by the business together with checking the temperature and dampness levels. If any of the parameters transcends the most extreme security edge, the concerned business authority will be informed. The safety of the industry is ensured by integrating information from various sensors. The system is consistent and steady. It is the best and most prudent method for hardware security observing.