An IoT-based Optimized Watering System for Plants

Kai-yu Tsang, Zuneera Umair, U. Qureshi, I. Zwetsloot
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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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基于物联网的植物优化浇灌系统
由于人口增长导致的消费增加,食品工业一直面临着食品的极度短缺。粮食短缺的主要原因之一是作物和植物的供水不足。通常,农民在没有评估植物的实时状况的情况下就制定了供水时间表,这导致了大量的水浪费。因此,植物有时浇水不足,有时浇水过多。在本文中,我们提出了一种基于物联网的植物浇水系统,该系统使用微控制器、土壤湿度传感器、环境温度传感器和湿度传感器来评估植物生长的有利条件。我们提出了4种不同的实验设置,包括室内和室外设置的常规浇水时间表设置和修改的浇水时间表设置。我们观察到,根据植物的生长情况,对植物进行适当的浇水,以最少的水量促进植物的生长。我们进一步对系统中不同的变量进行回归分析,观察对植物生长有直接影响的因素。根据我们的数据分析,环境温度和充足的水供应对植物的生长起着最重要的作用。
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