Go home now Header Background Image
Search
Submission Procedure
share: |
 
Follow us
 
 
 
 
Volume 24 / Issue 3

available in:   PDF (707 kB) PS (25 MB)
 
get:  
Similar Docs BibTeX   Write a comment
  
get:  
Links into Future
 
DOI:   10.3217/jucs-024-03-0302

 

Crowd Sensing for Urban Security in Smart Cities

Bruno Fernandes (University of Minho, Portugal)

Fábio Silva (University of Minho, Portugal)

Cesar Analide (University of Minho, Portugal)

José Neves (University of Minho, Portugal)

Abstract: Upcoming cities must undoubtedly reason upon the knowledge they have acquired through data gathered by sensorization. Those who do that will be at the forefront, closing to become Smart Cities. To achieve this goal, we must evolve from an Internet of Things to an Internet of People, defined as an ecosystem where everyone and everything can sense the other and the world, and act upon such data and knowledge, aiming to enhance people's quality of life. Considering the Vulnerable Road Users' (VRUs) problem, this work provides a proof of concept on crowd sensing for urban security in Smart Cities, confirming that our concept is viable and has practical potential. The goal is to sense the density of people at certain points of interest for VRUs, such as pedestrian crossings or busier roads, by detecting Wi-Fi probe requests with a Smart Scanner. Such information can be relevant to many applications, allowing, for example, the promotion of better safety measures on crowed spots, enhance crowd control and assemble interesting insights on traffic characteristics. To complement this work, and considering that smart clothing will certainly play an important role in promoting the citizen sensor and the smart cities' approach to VRUs' safety, a case study will be presented and discussed in which their clothing is equipped with a Bluetooth Low Energy transmitter. This allows such users to be recognized on the road, which may help avoid dangerous situations. The proof of concept was a success, with the developed software showing promising results at an extremely low price.

Keywords: ambient intelligence, crowd sensing, internet of people, smart cities, smart clothing, vulnerable road users

Categories: D.0, I.2.1, I.2.m, K.4.0