https://github.com/sandialabs/chama
Python package for sensor placement optimization
https://github.com/sandialabs/chama
optimization pyomo scr-2146 sensors snl-applications
Last synced: about 1 year ago
JSON representation
Python package for sensor placement optimization
- Host: GitHub
- URL: https://github.com/sandialabs/chama
- Owner: sandialabs
- License: other
- Created: 2016-10-25T15:59:10.000Z (over 9 years ago)
- Default Branch: main
- Last Pushed: 2024-09-03T22:47:47.000Z (almost 2 years ago)
- Last Synced: 2025-03-30T18:51:09.268Z (about 1 year ago)
- Topics: optimization, pyomo, scr-2146, sensors, snl-applications
- Language: Python
- Homepage:
- Size: 1.9 MB
- Stars: 66
- Watchers: 11
- Forks: 26
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
Awesome Lists containing this project
README

=========================================
[](https://github.com/sandialabs/chama/actions/workflows/build_tests.yml)
[](https://coveralls.io/github/sandialabs/chama?branch=main)
[](https://github.com/sandialabs/chama/actions/workflows/build_docs.yml)
[](https://pepy.tech/project/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 used.
The physical placement of these sensors and the sensor technology used can have
a large impact on the performance of a monitoring strategy.
Chama is a Python package which includes mixed-integer, stochastic
programming formulations to determine sensor locations and technology that maximize
the effectiveness of the detection program.
The software was developed to design sensor networks for water distribution networks and airborne pollutants,
but the methods are general and
can be applied to a wide range of applications.
For more information, go to https://sandialabs.github.io/chama/
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.
License
------------
Revised BSD. See the LICENSE.txt file.
Organization
------------
Directories
* chama - Python package
* ci - Travis CI requirements
* documentation - User manual
Contact
-------
* Katherine Klise, Sandia National Laboratories, kaklise@sandia.gov
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.