Sensor Placement Optimization using Chama¶
Continuous or regularly scheduled monitoring has the potential to quickly identify changes in the environment. However, even with low-cost sensors, only a limited number of sensors can be deployed. The physical placement of these sensors, along with the sensor technology and operating conditions, can have a large impact on the performance of a monitoring strategy.
Chama is an open source Python package which includes mixed-integer, stochastic programming formulations to determine sensor locations and technology that maximize monitoring effectiveness. The methods in Chama are general and can be applied to a wide range of applications. Chama is currently being used to design sensor networks to monitor airborne pollutants and to monitor water quality in water distribution systems.
To cite Chama, use the following reference:
- Klise, K.A., Nicholson, B., and Laird, C.D. (2017). Sensor Placement Optimization using Chama, Sandia Report SAND2017-11472, Sandia National Laboratories.
Indices and tables¶
Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525.