Remote tending of modern broadcast transmitters

Once broadcast transmitters are put into operation, regulatory bodies in different countries require the equipment to be monitored, data logged and controlled. Normally, transmitter personnel turn ON the transmitter at the start of the broadcasting activities, and turn it OFF at the end of the activities. They also regularly record the transmitter meter readings on output power, voltage and current as long as the transmitter is on-air. These data must be logged and saved for future references. These procedures are done by transmitter personnel manually. With the advent of internet technology, this paper presents a system to remotely monitor, gather and record meter readings, and a provision to control the turning ON/OFF as well as to adjust the output power of a number of digital transmitters. All these procedures are done in one central location. The system was implemented and then tested using a digital television transmitter. Results of the tests show that the developed system capable of performing the functions of a transmitter technician in monitoring, logging and control of broadcast transmitters remotely. With the use of the system, broadcast networks can reduce operating costs in tending their transmitters but still able to comply with the requirements. © 2019 Institute of Advanced Engineering and Science. All rights reserved

Portable semi-autonomous robot for agricultural insect pest recognition and elimination

The agricultural sector is an important factor in society. The crops and livestock that can be harvested every year are the necessary materials needed for survival. The harvesting of crops could be a tedious task especially if not well maintained. Chances of missing a pest can be very high risking the crop itself. This project aims to ease the farmers when it comes to their tasks by introducing autonomy by creating a prototype that can move semi - autonomously and detect pests using computer vision. Using Jetson Nano, Arduino Mega, and Arduino Uno, and camera vision to recognize pests using YOLOv5, the system will be integrated to produce a system that can recognize, classify, and eliminate pests. A graphical user interface was developed to manually control the system and allow it to run autonomously