Wireless Multi-Sensor Networks for Smart Cities: A Prototype System with Statistical Data Analysis
This work addresses data management issues for smart city initiatives, but it is incremental as it applies existing statistical methods to a new prototype system.
The paper tackles the challenge of urban data integration for smart cities by developing a prototype system in Budapest that uses wireless multi-sensor networks on public lighting to gather data, with a cloud-based module that handles inconsistent data and provides short-term forecasts and smoothed maps with reliability estimates.
As urbanization proceeds at an astonishing rate, cities have to continuously improve their solutions that affect the safety, health and overall wellbeing of their residents. Smart city projects worldwide build on advanced sensor, information and communication technologies to help dealing with issues like air pollution, waste management, traffic optimization, and energy efficiency. The paper reports about the prototype of a smart city initiative in Budapest which applies various sensors installed on the public lighting system and a cloud-based analytical module. While the installed wireless multi-sensor network gathers information about a number of stressors, the module integrates and statistically processes the data. The module can handle inconsistent, missing and noisy data and can extrapolate the measurements in time and space, namely, it can create short-term forecasts and smoothed maps, both accompanied by reliability estimates. The resulting database uses geometric representations and can serve as an information centre for public services.