IoT based Computing to Monitor Indoor Plants by using Smart Pot

Abstract

The indoor plants are high in demand and the number of people buying indoor plants is increasing day by day. But people face a lot of problems in raising the indoor plants as taking care of these indoor plants is not easy and they even die with a cause which is difficult to predict. According to the National Gardening Association people from all age groups ranging 20 and above are completely obsessed with indoor plants. It states that in the US alone the sale of indoor plants has incremented by 50% during the last three years which now stands at a value of $1.7 billion in 2019. Barometer of Trade report shows the sale of indoor plants in India went up by 24.1% in a span of one year from 2016 to 2017. The market of indoor plants is increasing day by day so is the problem to take care of these plants. To raise and maintain the health of the indoor plants there are various factors that need to be monitored which include- soil moisture, sunlight, temperature, humidity, and soil pH. It is really difficult to monitor all of these factors manually. Therefore, our goal is to achieve automation in taking care of the houseplants by using various components (Arduino Nano, soil moisture sensor, submersible mini water pump, ESP8266 Wi-Fi module, BH1750 sensor, DHT11 sensor, pH sensor, water level sensor, and LiPo rechargeable battery, LED light) embedded in the Smart Pot and by creating a library of indoor plants with all its data points, so, that the Smart Pot works in accordance with the plant selected. It provides functionalities for automatic water pumping into plant soil in the right amount, sends a notification when the level of water in the storage tank of the pot is low, sends a notification to put the plant in the sunlight and to brings it back, uploads data on the cloud using internet through Wi-Fi. The data includes humidity, temperature, moisture, sunlight and pH value which can be seen through the android application and important notifications are sent if the value of a data point is not healthy. It also shows the overall health of the plant in its mobile interface.