An IoT-Powered Naval Defense against Bat Attacks in Indian Fruit Crops, an Effective Precaution against Nipah Virus

Fruit bats, often known as flying foxes, are essential pollinators and seed dispersers in many environments. It is critical for ecological research and conservation efforts to study their behaviour and population dynamics. The article investigates the application of machine learning approaches to automate the detection and interpretation of fruit bats by using ultrasonic sound ranges of fruit bats, allowing for non-invasive monitoring and data collecting. Fruit bats can cause damage to fruit farms; however, we can employ IoT sensor networks and powerful machine-learning technologies to quickly identify and prevent fruit bat attacks in fruit plantations in India. Machine learning techniques can be used to identify and analyses ultrasonic (beyond the range of human hearing) noises. This is very significant in domains such as biology (for example, bat echolocation), industrial inspection (for example, identifying ultrasonic equipment abnormalities), and others. Developing an IoT network to identify fruit bats using ultrasonic noises includes several technologies, including IoT devices, ultrasonic sensors, data processing, and machine learning.