Following a 2019 study by Weisheng Lu of Hong Kong University, big data was successfully mined in order to identify illegal construction waste dumping. Inspired by the successes of big data in combating other forms of urban crime, Lu devised an Illegal Dumping Filter to identify cases of dumping and their suspected perpetrators. Using publicly available data from Hong Kong waste disposal records, more than 9 million waste records from 2011 to 2017 were analyzed. The big data structure for the filter consisted of the following databases: (1) government construction waste management (CWM) facilities; (2) projects which dumped into the CWM facilities; (3) waste disposal by the truckload; (4) vehicles involved in the transport of waste.
Out of the over 9 million waste disposal records, 546 suspected trucks of illegal waste were identified. Successful data mining then led Lu to establish a tri-fold identification methodology: ‘Behavior characterization’ (defining the target criminal behaviour), ‘Big data analytical model development’ (creating the big data structure), and ‘Model training, calibration, and evaluation’ (mining the data). While the Hong Kong case study showcases the vast potentials of data mining to identify pollution-related criminal offences, the proposed infrastructure and methodology still needs to be tested for other applications.
Lu, W. (2019). Big data analytics to identify illegal construction waste dumping: A Hong Kong study. Resources, Conservation and Recycling, 141, 264-272. Retrieved from https://www.sciencedirect.com/science/article/abs/pii/S092134491830412
Categories
Citizen Science, Data, Pollution, Regulation
Air Pollution Robot
The dangers of air pollution to human health are well documented, though the traditional methodology of collecting and reporting on sample lags behind the need to keep abreast and regulate air pollution in a meaningful amount of time. The use of drones and robots have been identified by researchers as resources that can be tweaked […]
Artificial Life, Biodiversity, Climate Change, Ecological Monitoring, Industry/Natural Commodities, Lifestyle, Monitoring
Telematic Rivers
Erica Kermani’s artwork seeks to answer a central question: if rivers were seeing an equal, living entity, would humans take issues like climate change threatening them more seriously? In his year-long art exhibition in 2017, Kermani, in collaboration with Diana Salcedo & Jeana Chesnik, created a new forum of interaction between humans and rivers to […]
Climate Change, Ecological Monitoring, Lifestyle, Monitoring, Pollution, Visual Technologies
Co-occupied Boundaries
Art is easily found in nature but rarely is what considered art today inherently natural. The concept of co-occupied mediums that serve to be both functional for nature and aesthetically pleasing to people is being actively explored by Asya Ilgun and Phil Ayres, from the CITAstudio at The Royal Danish Academy of Fine Arts. In […]
Climate Change, Ecological Monitoring, Lifestyle, Monitoring, Pollution, Visual Technologies