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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
------------
.. toctree::
   :maxdepth: 1
	
   overview
   installation
   simulation
   sensors
   impact
   optimization
   graphics
   examples
   license
   whatsnew
   developers
   apidoc/chama
   reference

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
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`

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.