IoT Smart Agriculture for Aquaponics and Maintaining Goat Stall System

Abstract

This research presents project development on smart farm and agriculture. The surge in global population is compelling a shift towards smart farm and agriculture practices. This coupled with the diminishing natural resources increase in unpredictable weather conditions makes food security a major concern for most countries. As a result, the use of the internet of things (IoT) and data analytics (DA) are employed to enhance the operational efficiency and productivity in the farm and agriculture sector. The objective is to design a prototype that used the internet of things on the farm and agriculture. Next is to have a monitoring and controlling or automation system that will benefit the farmer. Then collect all the data to be analyses on the rainfall, temperature, humidity, and light intensity. The methodology comprised of hardware, software, programming, sensors such as water sensor, light depending resistor sensor, temperature, and humidity sensor, and weight sensor for collected data. The result presents a prototype on aquaponics and goat stall that implement the concepts of the internet of things for monitoring, controlling, or automation system while data analytics is presented from all the sensors. Analytic data on the temperature, light intensity, humidity, and rainfall rate are analyzed. Surrounding temperatures are important for both plants and fish because if it too hot, they can die easily. The optimum light is needed by the plant for their photosynthesis process. Thus, by monitoring and collecting these parameters, data can be used for analyzing purposes. This project can benefit the agriculture and farm sectors in a larger or small scale.

A review on internet of things-based stingless bee's honey production with image detection framework

“…This makes it feasible to acquire various information and to monitor remotely in real time. The next agricultural revolution, especially in precision agriculture, will be largely dependent on machine learning (ML) and the IoT [13]- [15]. Human labor can be minimized by using machine learning models using sensor data and clever approaches [16].…”