Precision agriculture monitoring system using wireless sensor network and Raspberry Pi local server

Author(s):  
Kristoffer O. Flores ◽  
Isidro M. Butaslac ◽  
Jon Enric M. Gonzales ◽  
Samuel Matthew G. Dumlao ◽  
Rosula S.J. Reyes

Workshop contamination can lead to changes in the characteristics of the air. Welding process for example inside the workshop will generate different pollutants just like fume and gases. These gases may threat the environment. Also the direct exposure of these gases by people inside the workshop may be considered as a risk on their health. For all reasons mentioned above air pollution monitoring system is important issue to decrease the risk of low level of health. This paper introduces the implementation of wireless sensor network to monitor a workshop air pollution. The proposed system prototype contains a set of gas sensors (CO, H2, NH3, Butane, Propane, Ethanol and NO2) which are deployed on stack and infrastructure of Wireless sensor Network. These sensors are calibrated using appropriate calibration technologies. They are controlled by ARDUINO based microcontroller. Also there is the main server which Installed on raspberry pi 3 and contains the main database of the system which supports real time management strategies by using the web interface to monitor the air pollution in form of numbers and charts. Sensors which controlled by ARDUINO platform are connected to the server using the wireless technology (Wi-Fi) and the communication is done by using Message Queuing Telemetry Transport protocol (MQTT).When the level of Carbon Monoxide gas is above the threshold the system will send an alert email to the department of the civil defense. The system is checked and tested in the training workshops of University of Technology to measure the levels of harmful gases which may harm the people in the workshops.


2016 ◽  
Vol 12 (05) ◽  
pp. 43 ◽  
Author(s):  
Yuhong Zhou ◽  
Yunfang Xie ◽  
Limin Shao

To solve the topology structure of a greenhouse environment-monitoring system and the ductility of joints, this study presents a design of a greenhouse-monitoring system based on the ZigBee wireless sensor network (WSN). The hardware and software designs of the network node are provided, and the process of the ZigBee network coordinator is elucidated. The system uses the microcontroller unit PIC18F4620CC2420 wireless transceiver module to send and receive data. Data from temperature and humidity sensors are collected using an inter-integrated circuit bus through the ZigBee network transmission to the monitoring platform. Test results show that the system has the advantages of having a simple structure, flexible nodes, and low power consumption. It can effectively monitor the temperature and humidity in a wireless environment. WSNs considerably help in greenhouse environment monitoring. The use of advanced technology to control greenhouse temperature and humidity can satisfy the optimum growth environment of greenhouse crops and effectively improve the yield and quality of crops. The application of WSNs in greenhouse monitoring is significant to the development of modern and precision agriculture in China.


The higher the human population, the higher the demand for food supply from the agriculture sector. However, healthy and environment-friendly plant-based food production is very time-consuming. Water quality checking by the human resource is no longer efficient in the presence of technology today. Thus, a water quality monitoring system for aquaponics and fishpond is proposed in this study adapting the use of Wireless Sensor Network (WSN), Message Queuing Telemetry Transport (MQTT) protocol, and Wi-Fi signal. The completed system was successfully tested and implemented at the Malaysian Institute of Sustainable Agriculture (MISA). The devices send measurements to a base station which hosted a web server which can be viewed both locally and via the Internet. Results show the system is practical in use as it is both stable and reliable with 5 seconds maximum measurement refresh rate on its dashboard. Thus, reduces human dependency for monitoring the water quality of both the aquaponics and fishpond. Human resource can then be allocated to more crucial roles. Room for improvement includes complete use of solar renewable energy, adding Wi-Fi extender for large scale implementation, and equipping the Raspberry Pi with a cooling fan. This is the step forward to modernising agriculture.


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