AI-ENABLED REAL-TIME LOCATING AND RISK-INFORMED DECISION SUPPORT FOR ACCOUNTABLE LOCAL GOVERNANCE: AN ADAPTIVE WIRELESS SENSOR NETWORK FRAMEWORK

Povzetek

Effective local governance increasingly relies on dependable digital infrastructure, accurate asset monitoring, timely risk identification, and accountable public-service delivery.  Radio frequency interference, ground reflection and multipath propagation, however, can affect the positioning accuracy of such real-time locating systems (RTLS) based on wireless sensor networks (WSN) used in municipal buildings and facilities, leading to inaccurate estimations of the real-time location. These constraints can cause incomplete asset visibility, poor coordination in emergencies, poor planning of operations, and administration based on distorted facts. To overcome these challenges, this paper presents an adaptive WSN framework, which combines artificial neural network (ANN) -based localisation, the mitigation of ground-reflection error and a risk-informed decision support to local governance. The asset locations are estimated using a multilayer perceptron (MLP) that is able to learn the relationship between the characteristic of the transmitted wireless signals and reference positions, while an adaptive correction mechanism aims to enhance the asset's localisation stability under various propagation scenarios. Next, a multi-criteria risk prioritisation mechanism applies to the quantitative assessment of municipal operational risks, based on certain criteria that are set beforehand, such as the urgency, the disruption of services, the risk to safety and the requirement for the resources.This proposed research takes the traditional research on wireless positioning beyond the field of technical performance assessments and draws methodological linkages between wireless positioning reliability and public-sector decision making. The system endeavors to provide evidence based support at the local level by bridging the gap between the sensor intelligence level and operation risk assessment to aid municipal managers in asset management, emergency preparedness and service continuity. The results will feed into building reliable, transparent and accountable technology-enabled local governance systems.