We provide an in-depth study of applying wireless sensor networks (WSNs) to real-world habitat monitoring. A set of system design requirements were developed that cover the hardware design of the nodes, the sensor network software, protective enclosures, and system architecture to meet the requirements of biologists. In the summer of 2002, 43 nodes were deployed on a small island off the coast of Maine streaming useful live data onto the web. Although researchers anticipate some challenges arising in real-world deployments of WSNs, many problems can only be discovered through experience. We present a set of experiences from a four month long deployment on a remote island. We analyze the environmental and node health data to evaluate system performance. The close integration of WSNs with their environment provides environmental data at densities previously impossible. We show that the sensor data is also useful for predicting system operation and network failures. Based on over one million 2 Polastre et. al. data readings, we analyze the node and network design and develop network reliability profiles and failure models.

Habitat and environmental monitoring is a driving application for wireless sensor networks. We present an analysis of data from a second generation sensor networks deployed during the summer and autumn of 2003. During a 4 month deployment, these networks, consisting of 150 devices, produced unique datasets for both systems and biological analysis. This paper focuses on nodal and network performance, with an emphasis on lifetime, reliability, and the the static and dynamic aspects of single and multi-hop networks. We compare the results collected to expectations set during the design phase: we were able to accurately predict lifetime of the single-hop network, but we underestimated the impact of multihop traffic overhearing and the nuances of power source selection. While initial packet loss data was commensurate with lab experiments, over the duration of the deployment, reliability of the backend infrastructure and the transit network had a dominant impact on overall network performance. Finally, we evaluate the physical design of the sensor node based on deployment experience and a post mortem analysis. The results shed light on a number of design issues from network deployment, through selection of power sources to optimizations of routing decisions.

Habitat monitoring is an important driving application for wireless sensor networks (WSNs). Although researchers anticipate some challenges arising in the real-world deployments of sensor networks, a number of problems can be discovered only through experience. This paper evaluates a sensor network system described in an earlier work and presents a set of experiences from a four month long deployment on a remote island o# the coast of Maine. We present an in-depth analysis of the environmental and node health data. The close integration of WSNs with their environment provides biological data at densities previous impossible; however, we show that the sensor data is also useful for predicting system operation and network failures. Based on over one million data and health readings, we analyze the node and network design and develop network reliability profiles and failure models.

We provide an in-depth study of applying wireless sensor networks to real-world habitat monitoring. A set of system design requirements were developed that cover the hardware design of the nodes, the design of the sensor network, and the capabilities for remote data access and management. We propose a system architecture that addresses these requirements for habitat monitoring in general. We present an in-depth discussion of the implementation of the architecture for habitat monitoring. In the summer of 2002, 32 nodes were deployed on a small island off the coast of Maine streaming useful live data onto the web using our implementation. Results from the deployment show the profound impact software and hardware power management has on node longevity. The effectiveness of the system architecture is shown through the packet throughput and through the delivery of over 1.2 million readings logged at our database in Berkeley. The system operated for over four months; it provided data for two months after researchers had left the island for the winter due to poor weather conditions. The application-driven design exercise serves to identify important areas of further work in power management, data sampling, communications, network retasking, and health monitoring. We discuss the lessons learned from our deployment and provide a series of solutions that include new hardware, software, and protective enclosures.