Context aware wireless sensor system integrated with participatory sensing for real time road accident detection

Ramesh, Maneesha Vinodini; Vidya, P. T.; Pradeep, Preeja

doi:10.1109/wocn.2013.6616203

Cited by 12 publications

(8 citation statements)

References 5 publications

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“…In literature, a significant amount of work has been done on context-aware vehicular systems including smart parking, 7,25,26 accident detection, 3 driver behaviour, 5 driver assistance, 27 traffic congestion estimation, 2 and route planning and optimization. 6 Context-aware vehicular systems use the contextual information related to the drivers, the vehicle current states, traffic regulations, available parking lots at the specific parking area, and provide assisted support according to the current situation.…”

Section: Related Workmentioning

confidence: 99%

“…These systems provide variety of features to assist drivers ubiquitously about traffic condition, parking situation, and road safety, etc. [1][2][3][4][5][6][7] The design and development of these applications remain significantly more challenging in terms of complex and dynamic behaviour of the systems, more specifically in the safety-critical and emergency situations, and in hazardous environment. The reliability and trust of these applications could not be guaranteed without the support of model checking and formal verification techniques.…”

Section: Introductionmentioning

confidence: 99%

“…9 Using model checking and formal verification techniques, extremely large and complex systems can be traversed in minutes. In literature, a considerable amount of work has been done on context-aware transport systems in general, [1][2][3] and context-aware parking systems in particular. 7,10,11 Much of A preliminary version of this work has appeard in the proceedings of the 7th EAI International Conference on Context-Aware Systems and Applications (ICCASA'18).…”

Section: Introductionmentioning

confidence: 99%

“…Using model checking and formal verification techniques, extremely large and complex systems can be traversed in minutes. In literature, a considerable amount of work has been done on context‐aware transport systems in general, 1–3 and context‐aware parking systems in particular 7,10,11 . Much of the works aim at finding and reserving parking slots in advance at the designated places.…”

Section: Introductionmentioning

confidence: 99%

“…Context‐aware vehicular applications get contextual information related to the drivers, vehicle's current state (personalized information such as speed, acceleration, etc), traffic regulations, and take appropriate action according to the current situation. These systems provide variety of features to assist drivers ubiquitously about traffic condition, parking situation, and road safety, etc 1–7 . The design and development of these applications remain significantly more challenging in terms of complex and dynamic behaviour of the systems, more specifically in the safety‐critical and emergency situations, and in hazardous environment.…”

Section: Introductionmentioning

confidence: 99%

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A context‐aware framework for modelling and verification of smart parking systems in urban cities

Haque

Zulfiqar

Ahmed

et al. 2019

Concurrency and Computation

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Parking spaces have been considered as vital resources in urban areas. Finding parking spaces in jam-packed areas is often challenging, stressful, and uncertain for the drivers that causes traffic congestion with a consequent of wastage of time, fuel, and increase of pollution. In recent years, context-aware computing paradigm has been considered to be the most effective approach to address these kinds of issues. Context-aware systems acquire and understand contextual information according to the current situation, perform reasoning, and then act intelligently on behalf of the user. These applications often run on tiny resource-bounded smart devices with the incorporation of embedded or attached sensors on these devices and they often exhibit complex and adaptive behaviour. In this paper, we propose a context-aware parking application framework to assist drivers in finding parking slots dynamically while moving and/or arriving at the destination. We optimize the context-aware parking framework with bounds on computational resources for the decision support dynamically in a highly decentralized environment. To illustrate the use of the proposed system, we model the context-aware parking system using UPPAAL model checker for formal analysis and verify the correctness properties of the system.

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