CityWatch: exploiting sensor data to manage cities better

Manzoor, Atif; Patsakis, Constantinos; Morris, Alistair; McCarthy, Jessica; Mullarkey, Gabriel; Pham, Han; Clarke, Siobhán; Cahill, Vinny; Bouroche, Mélanie

doi:10.1002/ett.2786

Cited by 31 publications

(10 citation statements)

References 31 publications

(27 reference statements)

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“…The purpose of machine learning and reasoning is to monitor the behaviors of urban systems and citizens and the changes in their environment using sensors of many types to generate inferences (high-abstractions of contexts) based on reasoning mechanisms, and then use physical actors (actuators) or application actions to react and pre-act accordingly in ways that are more constructive in terms of enhancing urban operations, functions, and services in line with the goals of sustainable development. The widespread adoption of diverse sensors within cities provides interactions through opportunistic and people-centric sensing [99,100]. In this regard, context-aware applications can monitor what is happening in urban environments, analyze, interpret, and respond to them in a variety of ways-be it in relation to smart energy, smart street lights, smart traffic, smart transport, smart mobility, smart education, smart healthcare, or smart safety-across several spatial and temporal scales (e.g.…”

Section: Context Awareness Technology For Urban Sustainabilitymentioning

confidence: 99%

The core enabling technologies of big data analytics and context-aware computing for smart sustainable cities: a review and synthesis

Bibri

Krogstie

2017

J Big Data

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Data sensing, information processing, and networking technologies are being fast embedded into the very fabric of the contemporary city to enable the use of innovative solutions to overcome the challenges of sustainability and urbanization. This has been boosted by the new digital transition in ICT. Driving such transition predominantly are big data analytics and context-aware computing and their increasing amalgamation within a number of urban domains, especially as their functionality involve more or less the same core enabling technologies, namely sensing devices, cloud computing infrastructures, data processing platforms, middleware architectures, and wireless networks. Topical studies tend to only pass reference to such technologies or to largely focus on one particular technology as part of big data and context-aware ecosystems in the realm of smart cities. Moreover, empirical research on the topic, with some exceptions, is generally limited to case studies without the use of any common conceptual frameworks. In addition, relatively little attention has been given to the integration of big data analytics and context-aware computing as advanced forms of ICT in the context of smart sustainable cities. This endeavor is a first attempt to address these two major strands of ICT of the new wave of computing in relation to the informational landscape of smart sustainable cities. Therefore, the purpose of this study is to review and synthesize the relevant literature with the objective of identifying and distilling the core enabling technologies of big data analytics and context-aware computing as ecosystems in relevance to smart sustainable cities, as well as to illustrate the key computational and analytical techniques and processes associated with the functioning of such ecosystems. In doing so, we develop, elucidate, and evaluate the most relevant frameworks pertaining to big data analytics and context-aware computing in the context of smart sustainable cities, bringing together research directed at a more conceptual, analytical, and overarching level to stimulate new ways of investigating their role in advancing urban sustainability. In terms of originality, a review and synthesis of the technical literature has not been undertaken to date in the urban literature, and in doing so, we provide a basis for urban researchers to draw on a set of conceptual frameworks in future research. The proposed frameworks, which can be replicated and tested in empirical research, will add additional depth and rigor to studies in the field. In addition to reviewing the important works, we highlight important applications as well as challenges and open issues. We argue that big data analytics and context-aware Krogstie J Big Data (2017) 4:38 DOI 10.1186/s40537-017-0091-6 Data (2017) 4:38 computing are prerequisite technologies for the functioning of smart sustainable cities of the future, as their effects reinforce one another as to their efforts for bringing a whole new dimension to the operating and organiz...

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Section: Context Awareness Technology For Urban Sustainabilitymentioning

confidence: 99%

The core enabling technologies of big data analytics and context-aware computing for smart sustainable cities: a review and synthesis

Bibri

Krogstie

2017

J Big Data

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“…This can be understood more extensively from the viewpoint of IoT or ubiquitous computing. The role of wearables is not limited to just trackers of physical body status anymore; it can be extended to search for utilization methods by linking with external services after collecting various data about personal information generated by other apps and devices [35,36]. In this process, wearable technology will have a significant role in achieving objective value.…”

Section: Ambient Intelligence Internet Of Thingsmentioning

confidence: 99%

Sustainable Wearables: Wearable Technology for Enhancing the Quality of Human Life

et al. 2016

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This paper aims to elicit insights about sustainable wearables by investigating recent advancements in wearable technology and their applications. Wearable technology has advanced considerably from a technical perspective, but it has stagnated due to barriers without penetrating wider society despite early positive expectations. This situation is the motivation behind the focus on studies by many research groups in recent years into wearable applications that can provide the best value from a human-oriented perspective. The expectation is that a new means to resolve the issue can be found from a viewpoint of sustainability; this is the main point of this paper. This paper first focuses on the trend of wearable technology like bodily status monitoring, multi-wearable device control, and smart networking between wearable sensors. Second, the development intention of such technology is investigated. Finally, this paper discusses about the applications of current wearable technology from the sustainable perspective, rather than detailed description of the component technologies employed in wearables. In this paper, the definition of sustainable wearables is discussed in the context of improving the quality of individual life, social impact, and social public interest; those wearable applications include the areas of wellness, healthcare, assistance for the visually impaired, disaster relief, and public safety. In the future, wearables will not be simple data trackers or fun accessories but will gain extended objectives and meanings that play a valuable role for individuals and societies. Successful and sustainable wearables will lead to positive changes for both individuals and societies overall.

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“…Manzoor et. al., proposed the City Watch framework, which facilities the collection of information regarding "problematic areas" in a city to improve the city [11]. Users of the system can obtain points for competition among individuals or local communities by reporting hygienic problems, such as garbage left on the street or issues regarding improvement of the city's efficiency or safety, such as flooding at a regular bus stop.…”

Section: Related Workmentioning

confidence: 99%