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53
SignalGuru: Leveraging Mobile Phones for Collaborative Traffic Signal Schedule Advisory
"... While traffic signals are necessary to safely control competing flows of traffic, they inevitably enforce a stop-and-go movement pattern that increases fuel consumption, reduces traffic flow and causes traffic jams. These side effects can be alleviated by providing drivers and their onboard computat ..."
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Cited by 43 (4 self)
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While traffic signals are necessary to safely control competing flows of traffic, they inevitably enforce a stop-and-go movement pattern that increases fuel consumption, reduces traffic flow and causes traffic jams. These side effects can be alleviated by providing drivers and their onboard computational devices (e.g., vehicle computer, smartphone) with information about the schedule of the traffic signals ahead. Based on when the signal ahead will turn green, drivers can then adjust speed so as to avoid coming to a complete halt. Such information is called Green Light Optimal Speed Advisory (GLOSA). Alternatively, the onboard computational device may suggest an efficient detour that will save the driver from stops and long waits at red lights ahead. This paper introduces and evaluates SignalGuru, a novel software service that relies solely on a collection of mobile phones to detect and predict the traffic signal schedule, enabling GLOSA and other novel applications. Our SignalGuru leverages windshieldmounted phones to opportunistically detect current traffic signals with their cameras, collaboratively communicate and learn traffic signal schedule patterns, and predict their future schedule. Results from two deployments of SignalGuru, using iPhones in cars in Cambridge (MA, USA) and Singapore, show that traffic signal schedules can be predicted accurately. On average, SignalGuru comes within 0.66s, for pre-timed traffic signals and within 2.45s, for traffic-adaptive traffic signals. Feeding SignalGuru’s predicted traffic schedule to our GLOSA application, our vehicle fuel consumption measurements show savings of 20.3%, on average.
Will: Wireless indoor localization without site survey
- IEEE Trans. Parallel and Distributed Systems
, 2013
"... Abstract—Indoor localization is of great importance for a range of pervasive applications, attracting many research efforts in the past two decades. Most radio-based solutions require a process of site survey, in which radio signatures are collected and stored for further comparison and matching. Si ..."
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Cited by 17 (2 self)
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Abstract—Indoor localization is of great importance for a range of pervasive applications, attracting many research efforts in the past two decades. Most radio-based solutions require a process of site survey, in which radio signatures are collected and stored for further comparison and matching. Site survey involves intensive costs on manpower and time. In this work, we study unexploited RF signal characteristics and leverage user motions to construct radio floor plan that is previously obtained by site survey. On this basis, we design WILL, an indoor localization approach based on off-the-shelf WiFi infrastructure and mobile phones. WILL is deployed in a real building covering over 1600m2, and its deployment is easy and rapid since site survey is no longer needed. The experiment results show that WILL achieves competitive performance comparing with traditional approaches. I.
Parking slot assignment games.
- In GIS,
, 2011
"... ABSTRACT With the proliferation of location-based services, mobile devices, and embedded wireless sensors, more and more applications are being developed to improve the efficiency of the transportation system. In particular, new applications are arising to help vehicles locate open parking spaces. ..."
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Cited by 15 (7 self)
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ABSTRACT With the proliferation of location-based services, mobile devices, and embedded wireless sensors, more and more applications are being developed to improve the efficiency of the transportation system. In particular, new applications are arising to help vehicles locate open parking spaces. Nevertheless, while engaged in driving, travelers are better suited being guided to a particular and ideal parking slot, than looking at a map and choosing which spot to go to. Then the question of how an application should choose this ideal parking spot becomes relevant. Vehicular parking can be viewed as vehicles (players) competing for parking slots (resources with different costs). Based on this competition, we present a game-theoretic framework to analyze parking situations. We introduce and analyze Parking Slot Assignment Games (Psag) in complete and incomplete information contexts. For both models we present algorithms for individual players to choose parking spaces ideally. To evaluate the more realistic incomplete information Psag, simulations were performed to test the performance of various proposed algorithms.
Profit-maximizing incentive for participatory sensing
- in IEEE INFOCOM
"... Abstract—We design an incentive mechanism based on all-pay auctions for participatory sensing. The organizer (principal) aims to attract a high amount of contribution from participating users (agents) while at the same time lowering his payout, which we for-mulate as a profit-maximization problem. W ..."
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Cited by 15 (1 self)
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Abstract—We design an incentive mechanism based on all-pay auctions for participatory sensing. The organizer (principal) aims to attract a high amount of contribution from participating users (agents) while at the same time lowering his payout, which we for-mulate as a profit-maximization problem. We use a contribution-dependent prize function in an environment that is specifically tailored to participatory sensing, namely incomplete information (with information asymmetry), risk-averse agents, and stochastic population. We derive the optimal prize function that induces the maximum profit for the principal, while satisfying strict individual rationality (i.e., strictly have incentive to participate at equilibrium) for both risk-neutral and weakly risk-averse agents. The thus induced profit is demonstrated to be higher than the maximum profit induced by constant (yet optimized) prize. We also show that our results are readily extensible to cases of risk-neutral agents and deterministic populations. Index Terms—Mechanism design, Bayesian game, all-pay auc-tion, perturbation analysis, network economics, crowdsensing.
Advancing the State of Mobile Cloud Computing
"... The capabilities of mobile devices have been improving very quickly in terms of computing power, storage, feature support, and developed applications. However, these mobile applications are still intrinsically limited by a relative lack of bandwidth, computing power, and energy compared to their tet ..."
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Cited by 14 (0 self)
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The capabilities of mobile devices have been improving very quickly in terms of computing power, storage, feature support, and developed applications. However, these mobile applications are still intrinsically limited by a relative lack of bandwidth, computing power, and energy compared to their tethered counterparts. Cloud computing offers abundant computing power that can be tapped easily. Apple iCloud and Amazon Silk browser are two recent mobile applications that leverage the cloud. In this paper, we systematically explore the fundamental research questions when combining mobile and cloud computing. We will highlight some of the challenges we face and some of the solutions we are pursuing.
ParkSense: A Smartphone Based Sensing System For On-Street Parking
"... Studies of automotive traffic have shown that on average 30 % of traffic in congested urban areas is due to cruising drivers looking for parking. While we have witnessed a push towards sensing technologies to monitor real-time parking availability, instrumenting on-street parking throughout a city i ..."
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Cited by 13 (0 self)
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Studies of automotive traffic have shown that on average 30 % of traffic in congested urban areas is due to cruising drivers looking for parking. While we have witnessed a push towards sensing technologies to monitor real-time parking availability, instrumenting on-street parking throughout a city is a considerable investment. In this paper, we present ParkSense, a smartphone based sensing system that detects if a driver has vacated a parking spot. ParkSense leverages the ubiquitous Wi-Fi beacons in urban areas for sensing unparking events. It utilizes a robust Wi-Fi signature matching approach to detect driver’s return to the parked vehicle. Moreover, it uses a novel approach based on the rate of change of Wi-Fi beacons to sense if the user has started driving. We show that the rate of change of the observed beacons is highly correlated with actual user speed and is a good indicator of whether a user is in a vehi-cle. Through empirical evaluation, we demonstrate that our approach has a significantly smaller energy footprint than traditional location sensors like GPS and Wi-Fi based posi-tioning while still maintaining sufficient accuracy.
Short Paper: PEPSI: Privacy-Enhanced Participatory Sensing Infrastructure ABSTRACT
"... Participatory Sensing combines the ubiquity of mobile phones with the sensing capabilities of Wireless Sensor Networks. It targets the pervasive collection of information, e.g., temperature, traffic conditions, or medical data. Users produce measurements from their mobile devices, thus, a number of ..."
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Cited by 12 (0 self)
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Participatory Sensing combines the ubiquity of mobile phones with the sensing capabilities of Wireless Sensor Networks. It targets the pervasive collection of information, e.g., temperature, traffic conditions, or medical data. Users produce measurements from their mobile devices, thus, a number of privacy concerns – due to the personal information conveyed by reports – may hinder the large-scale deployment of participatory sensing applications. Prior work has attempted to protect privacy in participatory sensing, but it relied on unrealistic assumptions and achieved no provably-secure guarantees. In this paper, we introduce PEPSI: Privacy-Enhanced Participatory Sensing Infrastructure. We explore realistic architectural assumptions and a minimal set of formal requirements aiming at protecting privacy of both data producers and consumers. We also present an instantiation that attains privacy guarantees with provable security at very low additional computational cost and almost no extra communication overhead. Finally, we highlight some problems that call for further research in this developing area.
AccuLoc: Practical localization of performance measurements in 3G networks
- In ACM MobiSys
, 2011
"... Operators of 3G data networks have to distinguish the performance of each geographic area in their 3G networks to detect and resolve located network problems. This is because the quality of the “last mile ” radio link between 3G base stations and end-user devices is a crucial factor in the end-to-en ..."
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Cited by 11 (2 self)
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Operators of 3G data networks have to distinguish the performance of each geographic area in their 3G networks to detect and resolve located network problems. This is because the quality of the “last mile ” radio link between 3G base stations and end-user devices is a crucial factor in the end-to-end performance that each user experiences. It is relatively straightforward to measure the performance of all IP traffic in the 3G network from a small number of vantage points in the core network. However, the location information available about each mobile device (e.g., the cell sector/site that it is in) is often too stale to be accurate because of user mobility. Moreover, it is impractical to collect fine-grained location information about all mobile devices on an on-going basis in large 3G networks due to expensive measurement overhead. Thus, it is a challenge to accurately assign IP performance measurements to fine-grained
Towards cyber-physical systems in social spaces: The data reliability challenge,” in RTSS
- IEEE
"... Abstract—Today’s cyber-physical systems (CPS) increasingly operate in social spaces. Examples include transportation systems, disaster response systems, and the smart grid, where humans are the drivers, survivors, or users. Much information about the evolving system can be collected from humans in t ..."
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Cited by 8 (5 self)
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Abstract—Today’s cyber-physical systems (CPS) increasingly operate in social spaces. Examples include transportation systems, disaster response systems, and the smart grid, where humans are the drivers, survivors, or users. Much information about the evolving system can be collected from humans in the loop; a practice that is often called crowd-sensing. Crowd-sensing has not traditionally been considered a CPS topic, largely due to the difficulty in rigorously assessing its reliability. This paper aims to change that status quo by developing a mathematical approach for quantitatively assessing the probability of correctness of collected observations (about an evolving physical system), when the observations are reported by sources whose reliability is unknown. The paper extends prior literature on state estimation from noisy inputs, that often assumed unreliable sources that fall into one or a small number of categories, each with the same (possibly unknown) background noise distribution. In contrast, in the case of crowd-sensing, not only do we assume that the error distribution is unknown but also that each (human) sensor has its own possibly different error distribution. Given the above assumptions, we rigorously estimate data reliability in crowd-sensing systems, hence enabling their exploitation as state estimators in CPS feedback loops. We first consider applications where state is described by a number of binary variables, then extend the approach trivially to multivalued variables. The approach also extends prior work that addressed the problem in the special case of systems whose state does not change over time. Evaluation results, using both simulation and a real-life case-study, demonstrate the accuracy of the approach. I.
Lowering the Barriers to Large-Scale Mobile Crowdsensing
"... Mobile crowdsensing is becoming a vital technique for environment monitoring, infrastructure management, and social computing. However, deploying mobile crowdsensing applications in large-scale environments is not a trivial task. It creates a tremendous burden on application developers as well as mo ..."
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Cited by 7 (0 self)
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Mobile crowdsensing is becoming a vital technique for environment monitoring, infrastructure management, and social computing. However, deploying mobile crowdsensing applications in large-scale environments is not a trivial task. It creates a tremendous burden on application developers as well as mobile users. In this paper we try to reveal the barriers hampering the scale-up of mobile crowdsensing applications, and to offer our initial thoughts on the potential solutions to lowering the barriers. 1.
