Next century challenges: scalable coordination in sensor networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
System architecture directions for networked sensors
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Wireless sensor networks for habitat monitoring
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Introduction to Data Compression, Third Edition (Morgan Kaufmann Series in Multimedia Information and Systems)
WILDSENSING: Design and deployment of a sustainable sensor network for wildlife monitoring
ACM Transactions on Sensor Networks (TOSN)
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We present CARNIVORE, a system for in situ, unobtrusive monitoring of cryptic, difficult-to-catch/observe wildlife in their natural habitat. CARNIVORE is a network of mobile and static nodes with sensing, processing, storage, and wireless communication capabilities. CARNIVORE's compact, low-power, mobile animal-borne nodes collect sensor data and transmit it to static nodes, which then relay it to the Internet. Depending on the wildlife being studied, the network can be quite sparse and therefore disconnected frequently for arbitrarily long periods of time. To support "disconnected operation", CARNIVORE uses an "opportunistic routing" approach taking advantage of every encounter between nodes (mobile-to-mobile and mobile-to-static) to propagate data. With a lifespan of 50-100 days, a CARNIVORE mobile node, outfitted on a collar, collects and transmits 1 GB of data compared to 450 kB of data from comparable commercially available wildlife collars. Each collar records 3-axis accelerometer and GPS data to infer animal behavior and energy consumption.Testing in both laboratory and free-range settings with domestic dogs shows that galloping and trotting behavior can be identified. Data collected fromfirst deployments on mountain lions (Puma concolor) near Santa Cruz, CA, USA show that the system is a viable and useful tool for wildlife research.