Abstract
This paper is mainly aimed to develop a solar powered hand-held monitoring system for real-time crop-growth multiple environment parameter sensing and ZigBee-based wireless data transmission for Internet of Thing (IoT) applications. Regarding the problems of less man-power and difficult farm management in aging farmer population in many countries, in order to assist famers to monitor the status of plant growth and green-house condition in real time, this research focuses on the use of solar panels (5V/240mA 90mm2) and the buck converter IC to charge 18650 Lithium ion batteries used for hand-held monitoring system. The battery output will be coupled to a Low-Dropout (LDO) regulator, then generate a stable voltage to the CC2530 node. Solar panels will be integrated with the rechargeable batteries to yield more efficient power management. This paper proposes a LDO design for 18650 Lithium ion batteries. It will convert a supply voltage from 3.7V into 3.3V for driving the CC2530 and the sensors. The proposed solar powered system successfully built a Wireless Sensor Network (WSN) for quality agriculture application by using the ZigBee technology standard and TI’s CC2530 chip. Commercially available sensors were utilized specifically for temperature, humidity, soil moisture, light, chlorophyll, and CO2 monitoring. With the consideration and advantages of low power, low cost and multi-node capabilities, we chose ZigBee-based wireless network to transmit data into the cloud system for further data processing and analysis. When the sensors and Zigbee transmission system are set up, the data obtained through the human machine interface on the host will be sent to the cloud database established by MySQL in XAMPP. The management and data storage of the cloud database are both processed under the phpMyAdmin system. In addition, we use another program in XAMPP - Apache HTTP Server to set up the php website. Finally, this database of the sensing information will be used for assessment and evaluation of the environmental condition, data log recording, risk management and decision making. These resources can feed back to farmer’s cell phones through a decision support system. The experimental design and field test were verified in Tai-Yuan Organic farm located in Tao-Yuan County, Taiwan. The system will have a potential to be deployed into an open-field or green-house based farm to improve the optimized crop cultivation and increase the harvest yield. Figure 1
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