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Detection of Space and Time Patterns in the ECU 911 Integrated Security System Using Data Mining Techniques

Abstract:

The integrated security SIS ECU 911 will oversee monitoring emergency situations, video surveillance, and alarm monitoring reported through 911 services throughout the Ecuadorian territory. This research addresses space and time pattern detection at SIS ECU 911 (Imbabura-Ecuador) using mining data techniques to support decision-making processes in addition to operating costs. In 2018–2019, 47.4% of placed calls were ill-intentioned generating significant unnecessary operating costs. The study was conducted in four phases (i) caller location and call data gathering (ii) Creation of a Geo-database and hotspots (iii) Making of data clocks (iv) Pbkp_rediction model applying a Geo-graphical Weighted Regression (GWR). Hotspots determined that the largest number of ill-intentioned came from Ibarra and Otavalo cities. Data clocks showed a temporary pattern in the months of July and August as they are the most critical months. The GWR model identified that the rate for this type of phone call partially corresponds to a spatial predominant pattern that originated in the rural areas of Ibarra and Pimampiro. Therefore, all ill-intentioned calls respond to certain temporary spatial patterns that help us understand this problem aiming to pose mitigating alternatives.