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 linear programming formulations to determine sensor locations and technology that maximize monitoring effectiveness. Chama is currently being used to design sensor networks to monitor airborne pollutants and to monitor water quality in water distribution systems, however the methods in Chama are general and can be applied to a wide range of applications.

Contents

• Overview
• Installation
• Simulation
• Sensor technology
• Impact assessment
• Optimization
• Graphics
• Examples
• Copyright and license
• Release notes
• Software development
• API documentation
• References

Citing Chama

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

• Index

• Module Index

• Search Page

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.