Ragi Pest Control

Abstract

The rise of global population has put increasing pressure on the agriculture industry to meet the demand for food. However, the growing use of pesticides and insecticides in conventional farming practices has caused significant harm to the environment and human health. Thus, there is a growing interest in using sustainable agriculture practices that reduce the use of these harmful chemicals. One such practice is pest detection, which enables farmers to detect pests in their crops before they cause significant damage. In this context, this project aims to develop a pest detection system using IoT and Arduino. The system will be designed to detect pests in crops through a combination of sensors and machine learning algorithms. The system will consist of an Arduino microcontroller, soil moisture sensors, temperature and humidity sensors, infrared sensors or camera modules, and a Wi-Fi or Bluetooth module. The sensors will collect data on soil moisture levels, temperature, humidity, and pest activity. The data will be sent to a cloud-based server or database for analysis and visualization. The infrared sensor or camera module will detect the presence of pests in the crops. The system will use machine learning algorithms to distinguish between pests and other objects, such as leaves or debris. When pests are detected, the system will alert the farmer through a buzzer or LED connected to the Arduino board. The farmer can then take appropriate action, such as applying pesticide or removing infested plants. The pest detection system has the potential to reduce the use of harmful pesticides and insecticides in agriculture, as farmers will be able to identify pests before they cause significant damage. The system will also provide farmers with real-time information on pest activity, enabling them to take proactive measures to control pests and reduce crop damage. Additionally, the system can track and store the pest detection data over time, allowing farmers to monitor trends and patterns in pest activity. In conclusion, this project proposes the development of a pest detection system using IoT and Arduino that will enable farmers to monitor pest activity in their crops in real-time. The system has the potential to reduce the use of harmful chemicals in agriculture and improve crop yield while ensuring sustainable and environmentally friendly practices.