Enhanced Plant Monitoring System for Hydroponics Farming Ecosystem using IOT
Journal: GRD Journal for Engineering (Vol.5, No. 2)Publication Date: 2020-02-01
Authors : Deepika S; Vibesh V. Panicker; Annie Koshy; Shukriya Salim; Shimol Philip;
Page : 12-20
Keywords : Hydroponic Farming Ecosystem (HFE); Internet of Things;
Abstract
Hydroponics is an interesting way of cultivation where nutrients are effectively provided to the plants as mineral nutrient solutions. It requires much less space than any type of agricultural techniques. Hydroponics is the method of growing plants or vegetables without soil, but using mineral nutrient solutions mixed with water. This modern agriculture sector provides numerous advantages such as efficient location and space requirements, adequate climate control, and water-saving and controlled nutrients usage. This paper proposes a Hydroponic Farming Ecosystem (HFE) that uses IoT devices to monitor the environment of the hydroponic device through some sensors in a real-time and stable way, and then accurately, automatically transmit the data of temperature, humidity, light intensity, nutrient solution temperature, air temperature water level and pH in real-time. The Internet of Things (IoT) concept assumes that various “things,” which include not only communication devices but also every other physical object on the planet, are going to be connected and will be controlled across the Internet. The HFE is made to support non-professional farmers, city people who have limited knowledge in farming and people who are interested in doing vertical planting in very small areas in the city such as building roof, the balcony of high-rise buildings, and in small office spaces. To make the system easy to control and easy to use, we have an android application to control IoT devices in the HFE and alert users when their farm is in an abnormal situation. Therefore, the system is a valuable tool for hydroponics condition analytics and to support decision making on possible intervention to increase productivity. The results reveal that the system can generate a viable hydroponics appraisal, allowing to anticipate technical interventions that improve agricultural productivity.
Other Latest Articles
- Image Segmentation for Object Detection using Mask R-CNN in Colab
- Hand Gesture Recognition
- A Review on Role and Quality of Module Mounting Structure of Solar PV Power Plants Installed in India
- Women abuse Detection in Video Surveillance using Deep Learning
- FFT Computation for Butterfly Unit using Verilog HDL
Last modified: 2020-03-31 14:15:28