Intelligent Device for Borer Pest Trap in Sugarcane Culture

• Grant number: 23/15554-3
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: March 01, 2024
• End date: February 28, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Rodrigo Palucci Pantoni
• Grantee: Olavo Lampa Costa
• Host Institution: Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP). Campus Sertãozinho. Sertãozinho , SP, Brazil

Abstract

Technological evolution in recent years has led to the materialization of the so-called Internet of Things (IoT), whose main characteristic is to connect different objects to exchange information. Thus, due to the availability of 5G mobile data technology, which will allow the increase in the data transmission rate and the reduction of energy consumption of devices, it is possible to envisage a scenario of high connectivity of devices for different applications using technology. mobile data. In parallel to this scenario, the use of intelligent and automated techniques for pest control in agriculture has been rapidly evolving and adapted to this IoT world, especially in the case of insects, whose population control has been carried out through collection analysis. of individuals in traps, so that they can be analyzed to assess the application of insecticides only if necessary. In this context, this project's general objective is to design and implement a device to adapt to current traps used for the sugarcane borer (Diatraea saccharalis), so that it captures and transmits images via mobile data for analysis by a Neural Network. Convolutional, in order to detect the insect and the quantity found.