M2M-based Automated Greenhouse Monitoring System
The remote ecological monitoring group focuses on the development of a large-scale monitoring system for open-field orchards and automatic greenhouses. The intended purpose of the monitoring system is to reduce damage caused by insect pests and improve the agricultural productivity of orchards and greenhouses.
PI: Prof. Joe-Air Jiang
Champions: Yen-Kuang Chen
In this project, we plan to develop an M2M-based automated greenhouse monitoring system for boosting the productivity of growing orchids. Orchid greenhouse is chosen to be the monitoring target due to following reasons.
- Orchid is one of the essential economical crops in Taiwan.
- The export value of the orchid reaches 195 million US dollars in 2012 solely in Taiwan, which accounts for 93% of the total exports of flowers from the entire country.
- Taiwan is the top-2 orchid exporting country (behind Netherland), 1 out of 6 orchids in the world is produced in Taiwan.
Smart services –
(1) Pest monitoring and control – Bemisia tabaci (Gennadius), as known as Silverleaf Whitefly, is one of the major insects that could cause severe damage to the plants inside greenhouses. We plan to integrate cameras to observe the population size of Silverleaf Whitefly inside and outside the greenhouse. Modeling the population dynamics of Silverleaf Whitefly is of interest of the greenhouse owners. To understand better about the dynamics of pest population, we will deploy a camera and a monitoring station outside of the greenhouse. The camera is to observe the number of pest in outdoor environment, and the monitoring station is to record ambient conditions (temperature, humidity, light intensity, rainfall, etc.) These data will be used to uncover the dynamics of pest population outside of the greenhouse. Cameras will be used inside the greenhouse to monitor the distribution changes of pest, and also to analyze the correlation between pest populations inside and outside of the greenhouse. The model of the pest dynamics can serve as a reference for greenhouse owners to know when they have to pay extra care about their plants inside the greenhouse.
(2) Plant growth condition inspection & yield prediction – We also plan to install cameras at certain positions to observe the growth condition of the plant. Morphology and eco- physiological analysis method will be developed to screen the growth condition of every single plant on the plant tray. With this information, we can also help the greenhouse owner to predict seasonal yield of their product. Also, we will also use regular visible light cameras to analyze the morphological traits of the orchid leaves. By integrating this technology with the growth condition records, we can also find out the best indoor condition to cultivate the best quality 40 of plants. We can use this information to predict the seasonal yields of the greenhouse.
Members
Publications
C. Chuang et al., "Toward anticipating pest responses to fruit farms: Revealing factors influencing the population dynamics of the Oriental Fruit Fly via automatic field monitoring", Computers and Electronics in Agriculture, vol. 109, 11 2014, pp. 148–161.
C. Chen et al., "Efficient Coverage and Connectivity Preservation With Load Balance for Wireless Sensor Networks", IEEE Sensors Journal, vol. 15, no. 1, 2015, pp. 48-62.
C. Chen et al., "Performance measurement in wireless sensor networks using time-frequency analysis and neural networks", in 2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, pp. 1197-1201.
C. Chen et al., "TernCam: An automated energy-efficient visual surveillance system", International Journal of Computational Science and Engineering, vol. 9, 5 2014, pp. 44-54.
C. Chuang, J. Jiang, "ICT-based Remote Agro-Ecological Monitoring System A Case Study in Taiwan", Journal of Communication, Navigation, Sensing and Services (CONASENSE), vol. 1, 01 2014, pp. 67-92.
C. Cheng et al., "Adaptive coverage-preserving routing protocol for wireless sensor network", in 2013 Seventh International Conference on Sensing Technology (ICST), pp. 730-734.
J. Wan et al., "Determination of critical span in real time using proper orthogonal decomposition", in 2013 Seventh International Conference on Sensing Technology (ICST), pp. 816-821.
X. Wu, C. Chuang and J. Jiang, "Temperature Map Recovery Based on Compressive Sensing for Large-Scale Wireless Sensor Networks", in 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, pp. 1202-1206.
J. Jiang et al., "A Distributed RSS-Based Localization Using a Dynamic Circle Expanding Mechanism", IEEE Sensors Journal, vol. 13, no. 10, 2013, pp. 3754-3766.
J. Jiang et al., "Application of a web-based remote agro-ecological monitoring system for observing spatial distribution and dynamics of Bactrocera dorsalis in fruit orchards", Precision Agriculture, vol. 14, no. 3, Jun 2013, pp. 323-342.
