Sensor Placement Optimization using Chama
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Geotechnology and Engineering Dept.
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Discrete Math and Optimization Dept.
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. The following documentation includes installation instructions and examples, description of software features, and software license. The software is intended to be used by regulatory agencies, industry, and the research community. It is assumed that the reader is familiar with the Python Programming Language. References are included for addit ional background on software components. Online documentation, hosted at http://chama.readthedocs.io/, will be updated as new features are added. The online version includes API documentation .
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1405271
- Report Number(s):
- SAND-2017-11472; 658060
- Country of Publication:
- United States
- Language:
- English
Similar Records
Performance Monitoring using Pecos (V.0.1)
Chama v. 0.1 (beta version)