Project Proposed: This project, designing and implementing an energy efficient and reliable Wireless Sensor Network (WSN) for Urban Landscape Management System (ULIMS), aims to provide significant cost-savings and alleviate urban water shortage problem by combining WSNs, data management, system integration, and web-based delivery. The constructed WSN will consist of a long-lived, real-time reliable network with remote control capability. Based on engineer portable, low-energy sensor nodes that can provide sensed data, the resulting system (W-ULIMS) addresses fundamental constraints faced by WSNs deployed in outdoor harsh environments, including energy supply, limited memory, the need for unattended operation for a long period of time, and the lossy and transient behavior of WSN communication. The project presents the following activities: - Randomized scheduling with a connectivity guarantee, - Extremely low duty-cycle data forwarding, and - Remote control (using the idea of Trickle). The randomized scheduling with connectivity guarantee and extremely low-duty cycle data forwarding protocols under study are expected to collect sensor data in an energy efficient manner. The testbed provides an infrastructure to study practical estimation, data collection and dissemination, and energy conservation faced by WSNs in harsh environments.
Broader Impacts: This project applies new technologies to traditional agricultural environments and other applications while advancing the complex behaviors of WSNs. It should contribute to alleviate the significant water shortage problem facing many cities by providing cost-savings through efficient usage of agricultural labor and timely notification of situations requiring managerial decisions. Furthermore, it establishes an environment to broaden student?s knowledge and research experience.
Wireless Sensor Networks (WSNs) have become ideal candidates to provide effective and economically viable solutions to many potential applications. Unfortunately, the ability of WSNs to impact other research is still hampered by poor integration of WSNs into scientific and engineering disciplines. In this project, utilizing precision agriculture as an example application and focusing on addressing the fundamental operational challenges of WSNs when they are deployed under harsh outdoor environments, we present the design, implementation, and field deployment experience to integrate WSNs into precision agriculture – an application that could be greatly benefited by the cutting edge technology provided by WSNs. At the heart of our research is a designed WSN that will address various operational challenges, including link estimation, energy efficiency, reliable data collection, and data dissemination. Our project systematically studies reliable and energy efficient data collection protocols and data dissemination protocols for WSNs in a realistic environment. Specifically, because of the stringent power supply faced by WSNs, we have designed a randomized scheduling with connectivity guarantee protocol and low-duty-cycle data forwarding protocol to collect sensor data reliably in an energy efficient manner. We have also designed a remote control protocol based on the idea from the Trickle Algorithm. Utilizing the dominant open source embedded operating system TinyOS 2.x, popular wireless modules MicaZ/IRIS motes from Memsic Inc., data acquisition board MDA300CA from Memsic Inc., and soil moisture sensor probe ECHO EC5 from Decagon Devices Inc., we have constructed a prototype wireless sensor network for precision agriculture by integrating its application domain knowledge. To address the stringent power issues faced by WSNs, we have also designed a solar-powered WSN node, which will harness proliferate solar energy when the node is deployed outside. Utilizing Eko Environmental Monitoring systems from Memsic Inc. and the Wireless Sensor Network system from National Instruments, we have several field deployments in Texas A&M AgriLIFE Research Center, Beaumont, TX and Lamar University. Significant efforts are still required to maintain the deployed WSN system in order to make it function properly. Our research has demonstrated a great potential to alleviate water shortage problem and to revolutionize soil irrigation models through providing accurate in-situ data input for precision agriculture. As an interdisciplinary research project between researchers in Computer Science and Agriculture, our project will help understand complex WSN behaviors and provide researchers with valuable experience to design and implement WSN systems and protocols. An indoor WSN testbed based on TelosB motes and TinyOS 2.x have been established in the Department of Computer Science at Lamar University, Beaumont, TX. Various protocols can be designed and implemented using this test bed. This will greatly help WSN research and education. The open-source nature of our constructed WSN system has provided an excellent environment for students to study hands-on project of WSNs in teaching oriented universities. Our constructed WSN test bed will provide students with an excellent infrastructure to study practical link estimation, data collection, data dissemination, and energy conservation problems. Computer Science students will have great opportunities to study fundamental concepts of embedded operating systems, wireless networking protocols, software engineering, and database through building a realistic wireless sensor network.
