Next Article in Journal
A Novel PARAFAC Model for Processing the Nested Vector-Sensor Array
Next Article in Special Issue
Real Evaluations Tractability using Continuous Goal-Directed Actions in Smart City Applications
Previous Article in Journal
Stereo Camera Head-Eye Calibration Based on Minimum Variance Approach Using Surface Normal Vectors
Previous Article in Special Issue
Real-Time Traffic Risk Detection Model Using Smart Mobile Device
Open AccessArticle

Volunteers in the Smart City: Comparison of Contribution Strategies on Human-Centered Measures

1
Chair of Computational Social Science, ETH Zürich, Clausiusstrasse 50, 8092 Zürich, Switzerland
2
School of Computer Science and Statistics, Trinity College Dublin, Dublin 2, Ireland
3
Interactive Intelligence Group, TU Delft, Mekelweg 4, 2628 Delft, The Netherlands
4
LIACS, Leiden University, Niels-Bohr-Weg 1, 2333 CA Leiden, The Netherlands
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(11), 3707; https://doi.org/10.3390/s18113707
Received: 28 September 2018 / Revised: 20 October 2018 / Accepted: 26 October 2018 / Published: 31 October 2018
  |  
PDF [753 KB, uploaded 31 October 2018]
  |  

Abstract

Provision of smart city services often relies on users contribution, e.g., of data, which can be costly for the users in terms of privacy. Privacy risks, as well as unfair distribution of benefits to the users, should be minimized as they undermine user participation, which is crucial for the success of smart city applications. This paper investigates privacy, fairness, and social welfare in smart city applications by means of computer simulations grounded on real-world data, i.e., smart meter readings and participatory sensing. We generalize the use of public good theory as a model for resource management in smart city applications, by proposing a design principle that is applicable across application scenarios, where provision of a service depends on user contributions. We verify its applicability by showing its implementation in two scenarios: smart grid and traffic congestion information system. Following this design principle, we evaluate different classes of algorithms for resource management, with respect to human-centered measures, i.e., privacy, fairness and social welfare, and identify algorithm-specific trade-offs that are scenario independent. These results could be of interest to smart city application designers to choose a suitable algorithm given a scenario-specific set of requirements, and to users to choose a service based on an algorithm that matches their privacy preferences. View Full-Text
Keywords: participatory sensing; smart cities; public good; privacy; fairness participatory sensing; smart cities; public good; privacy; fairness
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Bennati, S.; Dusparic, I.; Shinde, R.; Jonker, C.M. Volunteers in the Smart City: Comparison of Contribution Strategies on Human-Centered Measures. Sensors 2018, 18, 3707.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top