The main target of this project is to design and develop a Smart Overvoltage and Undervoltage Protection System Using Arduino to protect the appliance from damage. Nowadays fluctuation in AC mains voltage is frequent in domestic houses and industries. The abnormal over and under voltages may be caused by some reasons such as sudden interruption of heavy load, thunder lightning, switching impulses etc. It can easily damage sensitive electronic parts in these conditions. It is so preferable to have a tripping system such as MCB, or MCCB to protect the appliances.
But we have built an advanced system here that can smartly control your whole house’s electric supply using the user’s choice. Yes, we can set our desired maximum and minimum voltage for our needs.
In today’s market, various types of smart Overvoltage and Undervoltage protection systems have come out. But these are a little bit costly. Our project aims at protecting the electrical equipment from over and under voltages using just an Arduino and voltage sensor at a low cost. Here we use the ZMPT101B voltage sensor which is more accurate than others also it is cost-effective.
Model Description:
The model simulates a three-phase power system and detects faults occurring on any of the phases. Using MATLAB/Simulink, the system monitors voltages and currents in each phase. When a fault occurs (such as line-to-line or line-to-ground fault), the model identifies the faulted phase and calculates the fault current. Protective relays can be integrated to trigger isolation of the faulty line, ensuring system stability and safety.
Simulation Results:
The simulation demonstrates fault detection within milliseconds of fault occurrence.
Waveform analysis shows voltage dips and current spikes corresponding to the fault event.
The system accurately identifies the faulted phase and magnitude, validating the effectiveness of the detection algorithm.
Graphical outputs of phase voltages and currents provide clear visualization of fault dynamics
Solar Power Agricultural Robot For Disease Detection and Soil Health Mapping for cauliflower farming .
This project focuses on developing a solar-powered agricultural robot designed to assist farmers by detecting crop diseases and monitoring soil health. The robot integrates sensors and image processing techniques to identify early signs of plant diseases, allowing timely intervention. It also measures key soil parameters such as moisture, pH, and nutrient levels to ensure optimal crop growth.
By using solar energy, the system is eco-friendly and self-sustaining, reducing the dependency on conventional power sources. This smart agricultural solution aims to improve crop yield, reduce manual labor, and promote sustainable farming practices.
Key Features:
Disease detection using camera and AI algorithms
Soil health monitoring with sensors (moisture, pH, nutrients)
Solar-powered operation for sustainability
Real-time data collection and reporting