Pollution Level Monitoring of High Voltage Transmission Line Insulators Using Leakage Current Bursts Using a Wireless Device PROJECT TITLE : Pollution Severity Monitoring of High Voltage Transmission Line Insulators Using Wireless Device Based on Leakage Current Bursts ABSTRACT: In this article, a smart wireless online device for the monitoring of the severity of contaminated insulators in high voltage transmission networks is described. As a result, the wirelessly developed monitor functions by continuously sensing the magnitudes of the leakage current bursts and calculating its average root-mean-square (RMS) value for every second or minute as the monitor software is calibrated. This is done in order to ensure accurate results. Regarding this matter, the monitor will transfer an alarm signal and send a warning message to the members of the maintenance crew in order for them to take the action necessary to wash the high voltage line insulators in a timely manner before the unexpected outage of the high voltage network has been occurring. This will take place if the monitor determines that the average of the leakage current RMS value corresponds to a probably significant scale of a power outage. The newly designed monitor is comprised of several primary components, including a solar power bank, a cloud-based data storage system, a cloud-based power bank, a cloud-based data storage system, a current transformer with a burden resistor, and a smart device (Mobile or tablet). These components can be put together in such a way that they function properly even in the absence of an external power supply. The proposed monitor has a number of advantages over the other monitoring tools, including low operating costs, simple manipulation, and straightforward calibration. It offers a high level of protection, it is a straightforward online platform, and it has an uncomplicated layout. After carrying out fifty tests, the developed monitor is put through its paces in the laboratory using insulators whose conductivity corresponds to a variety of pollution layers. The results show that the accuracy of the proposed monitor has reached 91.66 percent after the completion of these tests. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Realistic Deployment of ZigBee and LoRa-based Hybrid Wireless Sensor Networks for Search and Rescue Applications Message Scheduling in a Blockchain-Based IoT Environment Using an Extra Fog Broker Layer