Wireless Multi-Sensor Networks for Smart Cities: A Prototype System with Statistical Data Analysis

TL;DR

This paper presents a prototype wireless multi-sensor network in Budapest's smart city project, integrating data collection, statistical analysis, and forecasting to support urban management and public services.

Contribution

It introduces a novel cloud-based analytical module capable of handling noisy, inconsistent data and providing short-term forecasts and smoothed maps for urban monitoring.

Findings

Successful deployment of sensors on public lighting in Budapest

Effective statistical processing of noisy and missing data

Generation of reliable short-term forecasts and smoothed spatial maps

Abstract

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.