Rutgers, the State University of New Jersey

Stevens Institute of Technology

Richard P Martin

Marco Gruteser

Yingying Chen

Yan Wang

Jie Yang

Yanyong Zhang

Richard E Howard

Zhenhua Jia

Konstantinos Kleisouris

Systems and methods of applying a prediction model to metal oxide sensors that change their electric resistances in response to surrounding gas concentrations for predicting equilibrium state resistance values of the sensors. The method includes heating a metal oxide sensor to for a predetermined period of time for the metal oxide sensor to interact with a surrounding gas; sampling transient resistance values of the metal oxide sensor to obtain sampled transient resistance values; determining an electrical resistance of the metal oxide sensor in a chemical equilibrium state of the interaction of the metal oxide sensor and the surrounding gas via applying a neural network; and determining a concentration level of the surrounding gas at the chemical equilibrium state by mapping the determined electrical resistance to a corresponding concentration level of the surrounding gas.

Systems and methods for low-power gas monitoring

A method for determining the position in a vehicle of a first device in communication with a microprocessor may include receiving, at the microprocessor, a first set of inertial data from at least one sensor of the first device; receiving, at the microprocessor, a second set of inertial data from at least one sensor of a reference device disposed within the vehicle; and determining, using the microprocessor, the position of the first device in the vehicle by comparing the first set of inertial data with the second set of inertial data.

Systems and methods for detecting driver phone operation using vehicle dynamics data

A method of tracking a service queue using a single-point signal monitor in which at least one customer carries a wireless device may include: receiving a received signal strength from the wireless device as a trace; identify first segments of the trace containing mostly positive sloped received signal strength; identify second segments of the trace containing mostly negative sloped received signal; extract attributes from the first and second segments as child variables for two parent nodes in a Bayesian Network in which the two parent nodes respectively model a beginning of service and a leaving period for a service queue; and inputting the extracted attributes into Bayesian Network; and determining a beginning of service and leaving period using the Bayesian Network. The method may also include determining critical time points in a trace using a K-L divergence technique.

Tracking service queues using single-point signal monitoring

Systems and methods for detecting driver phone operation using device position and orientation data

The invention is a technique for performing sampling in connection with Markov Chain Monte Carlo simulations in which no attempt is made to limit the selected samples to a selected slice of the entire sample domain, as is typical in Markov Chain Monte Carlo sampling. Rather, samples are taken from the entire domain and any samples that fall below a randomly selected probability density level are discarded.

Method and apparatus for using bayesian networks for localization

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Metuchen, NJ, United States of America

Richard P Martin