Abundance estimators that account for imperfect detection, such as N-mixture models,
assume that detection of individuals is independent of abundance. Using spot-mapping and …

Robust models of wildlife population size, spatial distribution, and habitat relationships are
needed to more effectively monitor endangered species and prioritize habitat conservation …

In many detection applications with battery powered or energy-harvesting sensors, energy
constraints preclude the use of the optimal detector all the time. Optimal energy-performance …

Equipping everyday objects with sensing and computational capabilities creates the
potential to achieve context and situational awareness through the detection of natural …

This paper proposes a low-power acoustic sensor built using off-the-shelf components. To
reduce energy consumption, the ADC and the microphone's signal-conditioning circuit are …

Real-time detection of intermittent events requires continual monitoring and processing of
sensor data. A battery-powered device that supports multiple sensing modalities and …

Traditional distributed detection systems are often designed for a single target application.
However, with the emergence of the Internet of Things paradigm, next-generation systems …

Energy efficiency is highly desirable for sensing systems in the Internet of Things. A common
approach to achieve low-power systems is duty cycling, where components in a system are …

This paper presents a new Q-value approximation algorithm for joint sensor scheduling and
MAP state estimation in hidden Markov models. The proposed algorithm is motivated by the …

The development of models to account for variation in the probability of detection, such as N–
mixture models, have advanced methods of estimating wildlife abundance and resource …