Desarrollo de dispensador automático de alimento para tilapias utilizando esp32 cam

Abstract

The dispensers or commonly called smart feeders, were born from the idea of having healthier pets through proper feeding, distributed by rations. They were derived from the large aquaculture industries, which were looking for fish and seafood to enjoy good health and optimum weight, in order to maximize profits and reduce losses. In the case of pets, the aim is for them to be in good health in order to improve their quality of life and reduce veterinary expenses. Currently, there are many fish feeders in the market, which are disproportionate in size, often discouraging people to buy them, which leads to continue to maintain a manual feeding. Manual or traditional feeding can lead to abnormal pet behavior, and in the case of fish and shellfish production, to slow growth and mostly diseased stock. Currently, most fish and shellfish farmers have relied on experience and intuition for feeding or predicting disease. But this can be automated, thanks to advances in technology and artificial intelligence, which allow to automate processes, recognize objects, measure physical variables, among others, which will allow a better control of production. For the development of the program that will control the feeder, the programming language was used in the integrated development environment Arduino IDE, which uses the C++ language, which contains a wide variety of examples and versions available in its extensive ESP32 library. The prototype component, which is responsible for dispensing the fish feed, is composed of an FD RS550 motor, which will be activated through an L298N motor controller. In this way, it is easy to control the speed of the motor and to distribute the necessary voltage to the ESP32-CAM module. Energy autonomy has been considered for the development of the prototype, thanks to the use of a solar panel, which fulfills the functions of harnessing solar energy and recharging the battery, which will serve as a power source for the equipment. This degree work details the development of a prototype of an automatic food dispenser for tilapia using the ESP32-CAM module and using a battery as a power source, rechargeable through a solar panel. Using the Internet of Things, this device connects through a static IP address within a local WiFi network, to observe the behavior of the tilapia with the help of its integrated camera OV2640 and also to feed the specimens at the current time or within a programmable time range. It also includes a timer for the motor drive that will allow dispensing the required amount of feed from 5 to 160 grams. In addition, the artificial intelligence of the ESP32-CAM module was applied to detect the tilapias in real time, inside the breeding pool.