Internet of Things Sensors and Data Analytics Based Decision Support System for Smart Greenhouse

Abstract

A decision support model and system is proposed based on Internet of Things (IoT) sensors and data analytic for smart greenhouse. The smart greenhouse system monitors multiple environmental factors around it, analyzes climatic and soil condition data, and automates the irrigation process. We also create dashboards and applications that can monitor the sensed data and help users make decisions. The proposed system architecture model studies a practical method that can operate in a microprocessor, IoT sensor and wireless network environment to control a greenhouse. The mobile application and service prototype are implemented and evaluated. The test was conducted in a general indoor space. Data measured in real time by various sensors notifies the smartphone or smart watch as needed. Automatic indoor gardening was implemented by operating the fan when indoor air quality was deteriorated or the humidity was above the appropriate value. It was also confirmed that water was supplied through the automatic water pump according to the measured value of the soil sensor. Data monitoring of the system has been developed successfully. This system provides real-time data and status of the output. The sensor will monitor the system and the controller will manage the all the system’s decision and activities automatically. This research was successfully conducted. However, some improvements can be done for future works. First, dissemination of green computing techniques where IoT devices shall consume less amount of energy thus increase their life expectancy and increase the productivity. Second, Interoperability between IoT devices where devices should be capable to communicate with others from different genre so as the overall system.