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
J. Jiang et al., "An Embedded System-based Distributed Private Cloud - Taking Power Quality Monitoring as An Example", in Symposium on Electrical Power Engineering(中華民國第三十三屆電力工程研討會), 2012, pp. 2045 - 2052.
Y. Chang et al., "A data retransmitting mechanism for ecological monitoring system", in 2012 Fifth IEEE International Conference on Service-Oriented Computing and Applications (SOCA), pp. 1-6.
M. Liao et al., "Development of an autonomous early warning system for Bactrocera dorsalis (Hendel) outbreaks in remote fruit orchards", Computers and Electronics in Agriculture, vol. 88, 2012, pp. 1 - 12.
Y. Tseng et al., "A Remote Monitoring System for Plant Frost Detection in High Altitude Areas", in AFITA 2012 - 8th Asian Conference for Information Technology in Agriculture.
X. Zheng et al., "Development of a self-sustainable autonomous environmental monitoring system", in The 15th International Symposium on Wireless Personal Multimedia Communications, 2012, pp. 153-158.
J. Wang et al., "A novel multipoint direct-estimation method for the maximum power point tracking of photovoltaic modules under partially shaded irradiation conditions", in 2012 IEEE International Energy Conference and Exhibition (ENERGYCON), pp. 13-19.
J. Wang et al., "High-Precision RSSI-based Indoor Localization Using a Transmission Power Adjustment Strategy for Wireless Sensor Networks", in 2012 IEEE 14th International Conference on High Performance Computing and Communication 2012 IEEE 9th International Conference on Embedded Software and Systems, pp. 1634-1638.
C. Chen et al., "A Probablistic Load-Balancing Convergecast Tree Algorithm for Heterogeneous Wireless Sensor Networks", in 2012 IEEE 14th International Conference on High Performance Computing and Communication 2012 IEEE 9th International Conference on Embedded Software and Systems, pp. 1624-1628.
T. Lai et al., "A Novel Dynamic Convergecast Tree Generator for WSN-based Environmental Surveillance of Orchid Plantation", in 2012 IEEE 14th International Conference on High Performance Computing and Communication 2012 IEEE 9th International Conference on Embedded Software and Systems, pp. 1629-1633.
T. Lin et al., "Application of a reliable MAC protocol for the urban air quality monitoring system based on the wireless sensor network", in 2012 Proceedings of IEEE Southeastcon, pp. 1-6.
