{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Mano Z"],"funding":["Israeli Ministry of Environmental Protection","Israeli ministry of Science & Technology"],"pagination":["3808"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9147153"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["22(10)"],"pubmed_abstract":["Air pollution is one of the prime adverse environmental outcomes of urbanization and industrialization. The first step toward air pollution mitigation is monitoring and identifying its source(s). The deployment of a sensor array always involves a tradeoff between cost and performance. The performance of the network heavily depends on optimal deployment of the sensors. The latter is known as the location-allocation problem. Here, a new approach drawing on information theory is presented, in which air pollution levels at different locations are computed using a Lagrangian atmospheric dispersion model under various meteorological conditions. The sensors are then placed in those locations identified as the most informative. Specifically, entropy is used to quantify the locations' informativity"],"journal":["Sensors (Basel, Switzerland)"],"pubmed_title":["Information Theory Solution Approach to the Air Pollution Sensor Location-Allocation Problem."],"pmcid":["PMC9147153"],"funding_grant_id":["162-7-1","3-15628"],"pubmed_authors":["Mano Z","Fishbain B","Kendler S"],"additional_accession":[]},"is_claimable":false,"name":"Information Theory Solution Approach to the Air Pollution Sensor Location-Allocation Problem.","description":"Air pollution is one of the prime adverse environmental outcomes of urbanization and industrialization. The first step toward air pollution mitigation is monitoring and identifying its source(s). The deployment of a sensor array always involves a tradeoff between cost and performance. The performance of the network heavily depends on optimal deployment of the sensors. The latter is known as the location-allocation problem. Here, a new approach drawing on information theory is presented, in which air pollution levels at different locations are computed using a Lagrangian atmospheric dispersion model under various meteorological conditions. The sensors are then placed in those locations identified as the most informative. Specifically, entropy is used to quantify the locations' informativity","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 May","modification":"2025-04-18T23:00:17.7Z","creation":"2025-04-07T10:41:42.052Z"},"accession":"S-EPMC9147153","cross_references":{"pubmed":["35632218"],"doi":["10.3390/s22103808"]}}