Smart parking solutions for urban areas

Polycarpou, Elena; Lambrinos, Lambros; Protopapadakis, Eftychios

doi:10.1109/wowmom.2013.6583499

Cited by 95 publications

(45 citation statements)

References 19 publications

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“…The usage of automated instrumentation for on-street parking monitoring [11] has become popular in several cities around the world. In existing deployments, small sensing devices are usually placed in every parking spot to monitor large urban areas.…”

Section: Related Workmentioning

confidence: 99%

Data Analytics for Smart Parking Applications

Piovesan

Turi

Toigo

et al. 2016

Sensors

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We consider real-life smart parking systems where parking lot occupancy data are collected from field sensor devices and sent to backend servers for further processing and usage for applications. Our objective is to make these data useful to end users, such as parking managers, and, ultimately, to citizens. To this end, we concoct and validate an automated classification algorithm having two objectives: (1) outlier detection: to detect sensors with anomalous behavioral patterns, i.e., outliers; and (2) clustering: to group the parking sensors exhibiting similar patterns into distinct clusters. We first analyze the statistics of real parking data, obtaining suitable simulation models for parking traces. We then consider a simple classification algorithm based on the empirical complementary distribution function of occupancy times and show its limitations. Hence, we design a more sophisticated algorithm exploiting unsupervised learning techniques (self-organizing maps). These are tuned following a supervised approach using our trace generator and are compared against other clustering schemes, namely expectation maximization, k-means clustering and DBSCAN, considering six months of data from a real sensor deployment. Our approach is found to be superior in terms of classification accuracy, while also being capable of identifying all of the outliers in the dataset.

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Section: Related Workmentioning

confidence: 99%

Data Analytics for Smart Parking Applications

Piovesan

Turi

Toigo

et al. 2016

Sensors

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“…Parking operators try to adopt methodologies for improving their revenue while offering advanced facilities to their customers; parking space monitoring and advance parking reservation are currently deemed as highly valuable features [2].…”

Section: A Parking Managementmentioning

confidence: 99%

DisAssist: An internet of things and mobile communications platform for disabled parking space management

Lambrinos

Dosis

2013

2013 IEEE Global Communications Conference (GLOBECOM)

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People with disabilities face many issues when it comes to parking in urban areas which include the limited availability of spaces allocated for their use and the unauthorised usage of such spaces. This paper presents DisAssist which is a system designed and developed based on the principles brought forward by the Internet of Things and Smart Cities initiatives; it integrates sensors and smart phones along with wireless and mobile communications to provide for better utilisation and management of parking spaces allocated for use by people with disabilities. Through the use of DisAssist, people with disabilities may obtain realtime availability of parking slots in an area of interest, reserve a slot and authenticate themselves when parking assisting the authorities with usage monitoring for law enforcement as well as capacity planning purposes. Entitlement verification is possible through a multitude of ways enabling users to embrace technology at the level and format they wish.

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“…However, recent developments in wireless sensor networks and Industry 4.0 motivated the expansion of IoT applications to different domains such as the industrial Internet, smart cities, the smart grid and healthcare [2,3,4,5,6]. Manyika [7] argues that IoT technologies have the ability to reach a total economic value of $11.1 trillion by 2025, a value that is equivalent to approximately 11% of the world economy.…”

Section: Introductionmentioning

confidence: 99%

An Ontology-Based Cybersecurity Framework for the Internet of Things

Mozzaquatro

Agostinho

Gonçalves

et al. 2018

Sensors

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The use of sensors and actuators as a form of controlling cyber-physical systems in resource networks has been integrated and referred to as the Internet of Things (IoT). However, the connectivity of many stand-alone IoT systems through the Internet introduces numerous cybersecurity challenges as sensitive information is prone to be exposed to malicious users. This paper focuses on the improvement of IoT cybersecurity from an ontological analysis, proposing appropriate security services adapted to the threats. The authors propose an ontology-based cybersecurity framework using knowledge reasoning for IoT, composed of two approaches: (1) design time, which provides a dynamic method to build security services through the application of a model-driven methodology considering the existing enterprise processes; and (2) run time, which involves monitoring the IoT environment, classifying threats and vulnerabilities, and actuating in the environment ensuring the correct adaptation of the existing services. Two validation approaches demonstrate the feasibility of our concept. This entails an ontology assessment and a case study with an industrial implementation.

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Smart parking solutions for urban areas

Cited by 95 publications

References 19 publications

Data Analytics for Smart Parking Applications

Data Analytics for Smart Parking Applications

DisAssist: An internet of things and mobile communications platform for disabled parking space management

An Ontology-Based Cybersecurity Framework for the Internet of Things

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