10,244 research outputs found
SymbioCity: Smart Cities for Smarter Networks
The "Smart City" (SC) concept revolves around the idea of embodying
cutting-edge ICT solutions in the very fabric of future cities, in order to
offer new and better services to citizens while lowering the city management
costs, both in monetary, social, and environmental terms. In this framework,
communication technologies are perceived as subservient to the SC services,
providing the means to collect and process the data needed to make the services
function. In this paper, we propose a new vision in which technology and SC
services are designed to take advantage of each other in a symbiotic manner.
According to this new paradigm, which we call "SymbioCity", SC services can
indeed be exploited to improve the performance of the same communication
systems that provide them with data. Suggestive examples of this symbiotic
ecosystem are discussed in the paper. The dissertation is then substantiated in
a proof-of-concept case study, where we show how the traffic monitoring service
provided by the London Smart City initiative can be used to predict the density
of users in a certain zone and optimize the cellular service in that area.Comment: 14 pages, submitted for publication to ETT Transactions on Emerging
Telecommunications Technologie
Fairguard: Harness Logic-based Fairness Rules in Smart Cities
Smart cities operate on computational predictive frameworks that collect,
aggregate, and utilize data from large-scale sensor networks. However, these
frameworks are prone to multiple sources of data and algorithmic bias, which
often lead to unfair prediction results. In this work, we first demonstrate
that bias persists at a micro-level both temporally and spatially by studying
real city data from Chattanooga, TN. To alleviate the issue of such bias, we
introduce Fairguard, a micro-level temporal logic-based approach for fair smart
city policy adjustment and generation in complex temporal-spatial domains. The
Fairguard framework consists of two phases: first, we develop a static
generator that is able to reduce data bias based on temporal logic conditions
by minimizing correlations between selected attributes. Then, to ensure
fairness in predictive algorithms, we design a dynamic component to regulate
prediction results and generate future fair predictions by harnessing logic
rules. Evaluations show that logic-enabled static Fairguard can effectively
reduce the biased correlations while dynamic Fairguard can guarantee fairness
on protected groups at run-time with minimal impact on overall performance.Comment: This paper was accepted by the 8th ACM/IEEE Conference on Internet of
Things Design and Implementatio
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