The project focuses on the Raspberry PI framework used to prevent the spreading of plant disease. In pharmaceutical research, to monitor healthy crops, understanding and identifying leaf ailments becomes an important aspect of research. This is taken care of by image processing. In this project, k-means cluster algorithm is used for image analysis. This enables identifying natural plant sickness at their time of occurrence. This paper discusses the optimal strategy to recognize plant ailments with the help of picture preparing. The automatic detection of these ailments are sent immediately through emails and SMS to the proprietor.
Solar power is one of the most potential energy sources that can be channeled to a number of uses. With the automobile industry making the most, this paper discusses the charging of E-vehicles using solar panels with the main aim to reduce greenhouse gas emissions and fossil fuels. The maximum power is monitored by IoT devices and tracked using MPPT controller. The simulation model is designed using Proteus software. The whole setup is connected to the Arduino UNO R3, the battery level, generated and distributes an amount of the battery is viewed using an LCD.
