Smart Plant Health Control System

Abstract

Pest infestations are in the group of main issues farmers deal with. Detecting the infection manually in its early stages is a big challenge farmer’s face while interacting with pest attacks. The rapid spread of sickness is causing farmers to endure significant losses. This enormous Loss is unable to manage until the insect's invasion is handled physically. This approach aims to identify insect’s assaults in its early stages. This study suggests an automatic approach to recognize insect’s attacks and alerting farmers to infections. The RaspberryPi 3B is connected to humidity and temperature sensors for measurement. The plant’s pictures are taken for further processing. Later, we compare them with healthy images. We have compared the threshold values for humidity and temperature. When the readings of humidity and temperature in the acquired image surpass the threshold values that could be classified as an affected image. Because it differs from the healthy leaf that was sampled. The diseased leaf is recognized, finally, the agriculturist is notified via TWILIO. The affected leaf is identified, and the farmer is notified via the TWILIO. The real-time data are examined with the sample data.