Intelligent Technique for Smart Locust Swarm Detection and Prevention Shield for Agricultural Fields

Abstract

In today's world, the agriculture industry has a lot of room for growth by incorporating the newest technical progressions and decision support systems to have enough surplus food output to feed the growing population. To perform and monitor numerous agricultural tasks in the fields, smart devices, remote sensors, the Internet of Things (IoT), and UAVs/Drones can be utilized to meet market demand for food and sustain the planet's survival. Since ancient times, locust and pests have destroyed fields and caused considerable problems with food security. Both historical and modern literature has reported serious outbreaks. Innovative technologies, such as the Internet of Things (IoT), offer a lot of promise to improve agricultural operations. Farmers will be able to make more informed decisions in less time, allowing them to manage their crops more effectively while lowering costs and boosting yields. The offered paper covers several topics linked to IoT-based technologies, as well as the many types of devices and sensors that can be used to detect locust and prevent crop destruction. The Smart Locust Swarm Detection and Prevention Shield is a machine-assisted repellent system in which Speech Recognition Sensors are utilized to detect the voice of a locust swarm using a Noise Compensated Model capable of detecting the ideal vocal qualities even in loud environments. This paper explains the components required to detect the presence of a locust swarm, including Voice Recording sensors, Motor Module Controller, GSM Module, Microphone, Solar Panel Directional Speakers, and Voice Recognized Input Signal transmitted by the Motor Module Controller. This paper looks at how the IoT is being utilized in agriculture to achieve smart and precise farming. Conventional survey methods fell far short of delivering the accurate forecasting and ongoing locust tracking that was needed. Traditional survey methodologies fall far short of meeting the need for precise forecasting and real-time monitoring of locust occurrence. In this context, this paper presents a collection of IoT options for locust status monitoring. This paper has examined how smart and accurate farming was made possible by the internet of things in agriculture. Traditional survey techniques fell far short of providing the precise forecasting and real-time monitoring of locust occurrence that was required.