Deep Learning Smart Irrigation System with GSM

Tang, Hong Jing (2021) Deep Learning Smart Irrigation System with GSM. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Abstract

COVID-19 pandemic strikes hard on every economic sector including agriculture. The disease spread and safety restrictions cause limited human movement and less physical interaction with a human. Most agriculture activities will need to be shut down or limited by the authorities. Therefore, the decrement in the workforce leads to lesser productivity and profits for the agriculturer. The technology of Internet of Things (IoT) helps agriculture to monitor the condition of the crop with embedded devices, sensors, and deep-learning on the desired location. GRU network, a deep learning neural network that is good in handling long-term and short-term dependencies allows the forecasting of soil moisture, temperature, and humidity for enabling the monitoring system to meet the precision standard for agriculture production. This project's purpose is to maintain soil moisture at an optimal level to increase harvest production.