Tsang, Kai Yu, Umair, Zuneera, Mujtaba Qureshi, Umair, and Maria Zwetsloot, Inez (2022) An IoT-based Optimized Watering System for Plants. In: Proceedings of the IEEE International Conference on Industrial Informatics. pp. 257-262. From: INDIN 2022: IEEE International Conference on Industrial Informatics, 25-28 July 2022, Perth, WA, Australia.

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Abstract

The food industry has been facing extreme shortages of food as a result of higher consumption due to increasing population. One of the key reasons of food shortages is inadequate water supply to the crops and plants. Usually farmers setup a schedule to supply water without assessing the real-time condition of the plants, which leads to wasting water in substantial quantities. As a result, plants are sometimes under watered or over watered. In this paper, we propose an IoT based watering system for plants that uses a microcontroller, a soil moisture sensor, an environmental temperature sensor, and a humidity sensor to assess favourable conditions of a plant's growth. We propose 4 different experimental setups including regular watering schedules setups and modified watering schedule setups for both indoor and outdoor settings. We observe that watering the plants by a modified schedule based on the plants condition, the growth increases by using minimum amount of water. We further apply regression analysis on different variables in our system to observe the factors that have a direct effect on the growth of the plant. Based on our data analysis, environmental temperature plays the most important part in the growth of a plant along with adequate water supply.

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