Crowdsensing in Smart Cities

2015 ◽  
pp. 316-338 ◽  
Author(s):  
Paolo Bellavista ◽  
Giuseppe Cardone ◽  
Antonio Corradi ◽  
Luca Foschini ◽  
Raffaele Ianniello
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Smart Cities ◽  
Design Guidelines ◽  
Technical Data ◽  
Fine Grained ◽  
Living Lab ◽  
Widespread Availability ◽  
One Year ◽  
The University

The widespread availability of smartphones with on-board sensors has recently enabled the possibility of harvesting large quantities of monitoring data in urban areas, thus enabling so-called crowdsensing solutions, which make it possible to achieve very large-scale and fine-grained sensing by exploiting all personal resources and mobile activities in Smart Cities. In fact, the information gathered from people, systems, and things, including both social and technical data, is one of the most valuable resources available to a city's stakeholders, but its huge volume makes its integration and processing, especially in a real-time and scalable manner, very difficult. This chapter presents and discusses currently available crowdsensing and participatory solutions. After presenting the current state-of-the-art crowdsensing management infrastructures, by carefully considering the related and primary design guidelines/choices and implementation issues/opportunities, it provides an in-depth presentation of the related work in the field. Moreover, it presents some novel experimental results collected in the ParticipAct Crowdsensing Living Lab testbed, an ongoing experiment at the University of Bologna that involves 150 students for one year in a very large-scale crowdsensing campaign.

Crowdsensing in Smart Cities

2019 ◽  
pp. 893-915
Author(s):  
Paolo Bellavista ◽  
Giuseppe Cardone ◽  
Antonio Corradi ◽  
Luca Foschini ◽  
Raffaele Ianniello
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Smart Cities ◽  
Design Guidelines ◽  
Technical Data ◽  
Fine Grained ◽  
Living Lab ◽  
Widespread Availability ◽  
One Year ◽  
The University

The widespread availability of smartphones with on-board sensors has recently enabled the possibility of harvesting large quantities of monitoring data in urban areas, thus enabling so-called crowdsensing solutions, which make it possible to achieve very large-scale and fine-grained sensing by exploiting all personal resources and mobile activities in Smart Cities. In fact, the information gathered from people, systems, and things, including both social and technical data, is one of the most valuable resources available to a city's stakeholders, but its huge volume makes its integration and processing, especially in a real-time and scalable manner, very difficult. This chapter presents and discusses currently available crowdsensing and participatory solutions. After presenting the current state-of-the-art crowdsensing management infrastructures, by carefully considering the related and primary design guidelines/choices and implementation issues/opportunities, it provides an in-depth presentation of the related work in the field. Moreover, it presents some novel experimental results collected in the ParticipAct Crowdsensing Living Lab testbed, an ongoing experiment at the University of Bologna that involves 150 students for one year in a very large-scale crowdsensing campaign.

scholarly journals Towards a Living Lab for Enhanced Thermal Comfort and Air Quality: Analyses of Standard Occupancy, Weather Extremes, and COVID-19 Pandemic

2021 ◽  
Vol 9 ◽  
Author(s):  
Giulia Ulpiani ◽  
Negin Nazarian ◽  
Fuyu Zhang ◽  
Christopher J. Pettit
Keyword(s):  
Environmental Quality ◽  
Low Cost ◽  
Design Guidelines ◽  
Weather Extremes ◽  
Fine Grained ◽  
Occupancy Patterns ◽  
Living Lab ◽  
Spatial Coverage ◽  
Educational Buildings ◽  
Extreme Variability

Maintaining indoor environmental (IEQ) quality is a key priority in educational buildings. However, most studies rely on outdoor measurements or evaluate limited spatial coverage and time periods that focus on standard occupancy and environmental conditions which makes it hard to establish causality and resilience limits. To address this, a fine-grained, low-cost, multi-parameter IOT sensor network was deployed to fully depict the spatial heterogeneity and temporal variability of environmental quality in an educational building in Sydney. The building was particularly selected as it represents a multi-use university facility that relies on passive ventilation strategies, and therefore suitable for establishing a living lab for integrating innovative IoT sensing technologies. IEQ analyses focused on 15 months of measurements, spanning standard occupancy of the building as well as the Black Summer bushfires in 2019, and the COVID-19 lockdown. The role of room characteristics, room use, season, weather extremes, and occupancy levels were disclosed via statistical analysis including mutual information analysis of linear and non-linear correlations and used to generate site-specific re-design guidelines. Overall, we found that 1) passive ventilation systems based on manual interventions are most likely associated with sub-optimum environmental quality and extreme variability linked to occupancy patterns, 2) normally closed environments tend to get very unhealthy under periods of extreme pollution and intermittent/protracted disuse, 3) the elevation and floor level in addition to room use were found to be significant conditional variables in determining heat and pollutants accumulation, presumably due to the synergy between local sources and vertical transport mechanisms. Most IEQ inefficiencies and health threats could be likely mitigated by implementing automated controls and smart logics to maintain adequate cross ventilation, prioritizing building airtightness improvement, and appropriate filtration techniques. This study supports the need for continuous and capillary monitoring of different occupied spaces in educational buildings to compensate for less perceivable threats, identify the room for improvement, and move towards healthy and future-proof learning environments.

scholarly journals CitySpeed: A Crowdsensing-Based Integrated Platform for General-Purpose Monitoring of Vehicular Speeds in Smart Cities

Smart Cities ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 46-65 ◽  
Author(s):  
Daniel Costa ◽  
Adson Damasceno ◽  
Ivanovitch Silva
Keyword(s):  
Smart City ◽  
Urban Areas ◽  
Large Scale ◽  
Smart Cities ◽  
General Purpose ◽  
Software Application ◽  
Management Actions ◽  
Modern Cities ◽  
Time Period ◽  
Search Filters

The development of crowdsensing-based technologies has allowed for the use of smartphones in large-scale data collection for different scopes of applications, mostly in a transparent and ubiquitous way. When concerning urban areas and smart city initiatives, the collection and further analysis of information about the highest number of vehicles is of paramount importance, potentially supporting more efficient mobility planning and management actions in modern cities. In this context, this article proposes a public general-purpose platform for acquisition and visualization of vehicular speeds, which can then be exploited by any additional application. For that, a crowdsensing-based mobile software application was developed to collect instantaneous speeds provided by smartphone GPS, formatting and distributing this information to a database system. Such historical data can then be exported or visualized through a web-based comprehensive interface, which provides valuable data when planning traffic mobility in cities; for example, indicating areas with heavier traffic over a certain time period. Therefore, allowing the use of many different search filters and supporting data delivery in the JSON format, the CitySpeed platform can provide services not supported by popular applications, such as Waze and Google Maps, and potentially assist smart city initiatives in this area.

scholarly journals Resident assistant peer training : perceptions surrounding the use and effectiveness of experienced student leaders as trainers at one small private catholic university

2016 ◽  
Author(s):  
◽  
Tina F. Sheppard
Keyword(s):  
Large Scale ◽  
Qualitative Case Study ◽  
Training Model ◽  
Senior Resident ◽  
Resident Assistants ◽  
Resident Assistant ◽  
Catholic University ◽  
One Year ◽  
The University

This qualitative case study of one small private Catholic university in the northeast examines the perceptions of experienced (i.e. second to third year staff) and inexperienced (i.e. newly hired staff) student resident assistants. Specifically, this study focuses on the observations and insights of experienced and inexperienced staff as it relates to peer presented training and the overall training curriculum. The university employees a traditional training timeline with large-scale trainings occurring immediately prior to the opening of fall and spring semesters and smaller onehour trainings occurring throughout each semester. The resident assistant staff likewise follows a common model employing a number of new, first year resident assistants as well as a smaller number of second and third year resident assistants called senior residents assistants (the word "senior" implies the student staff member has at least one year of experience; it does not reference the student's academic year). The student to resident assistant ratio is a comfortable 30:1 with students living in traditional and suite style residence halls as well as apartments for upper-division students and graduates. Overall, the residential program studied is very similar to any number of other residential programs across the country. The one possible exception is the use of experienced student staff (senior resident assistants) to train inexperienced student staff (resident assistants). While this training model is not unique to the university of study, there are data to determine how common this model is, nor has there been any research related to the student staff perceptions of the effectiveness of such a model. The results of this qualitative case study reveal the training impressions of nine resident and senior resident assistants with the aim of understanding how they experienced training, their thoughts related to the use of peer presented trainers, and how they saw peer presented trainers influencing the overall staff experience. Three themes emerged: the use of experienced student staff as teachers, mentors, and supervisors. In this study I conclude the use of experienced student staff as teachers and mentors is both appropriate in this setting and desired by both experienced and inexperienced staff. However, the use of the experienced student staff position as supervisors is not viewed as appropriate by either experienced or inexperienced student staff and is cautioned against.

scholarly journals CITYWIDE ESTIMATION OF PARKING SPACE USING AERIAL IMAGERY AND OSM DATA FUSION WITH DEEP LEARNING AND FINE-GRAINED ANNOTATION

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 479-485
Author(s):  
C. Henry ◽  
J. Hellekes ◽  
N. Merkle ◽  
S. M. Azimi ◽  
F. Kurz
Keyword(s):  
Data Fusion ◽  
Urban Areas ◽  
Traffic Management ◽  
Large Scale ◽  
Private Property ◽  
Contextual Information ◽  
Aerial Imagery ◽  
Parking Space ◽  
Fine Grained ◽  
Actual Use

Abstract. Emerging traffic management technologies, smart parking applications, together with transport researchers and urban planners are interested in fine-grained data on parking space in cities. However, there are no standardized, complete and up-to-date databases for many urban areas. Moreover, manual data collection is expensive and time-consuming. Aerial imagery of entire cities can be used to inventory not only publicly accessible and dedicated parking lots, but also roadside parking areas and those on private property. For a realistic estimation of the total parking space, the observed use of multi-functional traffic areas is taken into account by segmenting not only parking areas but also roads according to their purpose. In this paper, different U-Net based architectures are tested for detecting all these types of visible traffic areas. A new large-scale, high-quality dataset of manual annotations is used in combination with selected contextual information from OpenStreetMap (OSM) to depict the actual use as parking space. Our models achieve a good performance on parking area segmentation, and we show the significant impact of OSM data fusion in deep neural networks on the simultaneous extraction of multiple traffic areas compared to using aerial imagery alone.

scholarly journals Bazaar in the 'Burbs: Infilling fine grain of activity in the course grain context of Paraparaumu

2021 ◽  
Author(s):  
◽  
Yan Xin Zhu
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Open Space ◽  
Early Career ◽  
Spatial Network ◽  
Urban Context ◽  
Modular Network ◽  
Fine Grained ◽  
Fine Grain ◽  
Spatial Hierarchy

<p>The regional townships of New Zealand are losing young people. The township of Paraparaumu, located along the Kapiti Coast, is no exception. As a sprawling, low-density suburban settlement with its town center being Coastlands Shopping Center - the local mall - there are few job opportunities available. As a result, many early career adults choose to settle elsewhere. Tasked with creating more opportunities, the Kapiti Coast District Council plans to build a new commercial district. To make space for it, this will be done by paving over a large expanse of wetland adjacent to the mall.  The premise of this thesis is that generating opportunities do not have to be large scale. In more dense urban areas where space is limited, many productive activities occur within the fine grain of a city. Wetlands are also recognized as a critical natural infrastructure and a valuable social amenity. Thus, instead of building large commercial facilities that have to occupy the wetland, the design in this thesis proposes a facility made up of a finer grain and infills the glut of car park spaces in front of Coastlands Mall. The parking spaces displaced will be relocated into a parking tower adjacent to the site.  The building type of the Bazaar was looked at in this thesis as a model, for it is fine-grained and also ingrained with its urban context. The spatial network of the Bazaar democratizes access. The spatial network of the Bazaar democratizes access, which is a direct contrast to the singular and hierarchical nature of the mall. The design adopts these ideas and expresses them through a network of modules on a tartan grid plan transforming the design into a rhythmic series of spaces that express compression and expansion, allowing it to be an interlinked network of interior and exterior spaces.  The grid is a powerful tool for organizing expanses of space though it is only useful in an architectural sense when accompanied by a fine-grained variation. Though the repetitive grid is suitable in plan, as a 3d form it quickly dissolves into monotony when repeated across a field. Similarly, the site itself is inherently charged with spatial hierarchy. Thus, localized adjustments of the roof and exterior details were made to break the monotony and rest the spatial hierarchy.  This thesis explores how fine grain activity can be integrated into a large-grained context through the use of an additive, modular network set on a grid. Though the research findings produced on expression of this in the design outcome, the idea of a dense, fine-grained modular network is applicable in any context that has large inactive open space to be filled.</p>

scholarly journals URBAN GROWTH SCENARIOS OF A FUTURE MEGA CITY: CASE STUDY AHMEDABAD

2016 ◽  
Vol III-2 ◽  
pp. 165-172 ◽  
Author(s):  
A. Lehner ◽  
V. Kraus ◽  
K. Steinnocher
Keyword(s):  
Remote Sensing ◽  
Urban Growth ◽  
Urban Areas ◽  
Large Scale ◽  
Smart Cities ◽  
Urban Migration ◽  
Indian Government ◽  
Urban Remote Sensing ◽  
Urban Growth Scenarios

The study of urban areas and their development focuses on cities, their physical and demographic expansion and the tensions and impacts that go along with urban growth. Especially in developing countries and emerging national economies like India, consistent and up to date information or other planning relevant data all too often is not available. With its Smart Cities Mission, the Indian government places great importance on the future developments of Indian urban areas and pays tribute to the large-scale rural to urban migration. The potentials of urban remote sensing and its contribution to urban planning are discussed and related to the Indian Smart Cities Mission. A case study is presented showing urban remote sensing based information products for the city of Ahmedabad. Resulting urban growth scenarios are presented, hotspots identified and future action alternatives proposed.

scholarly journals URBAN GROWTH SCENARIOS OF A FUTURE MEGA CITY: CASE STUDY AHMEDABAD

2016 ◽  
Vol III-2 ◽  
pp. 165-172
Author(s):  
A. Lehner ◽  
V. Kraus ◽  
K. Steinnocher
Keyword(s):  
Remote Sensing ◽  
Urban Growth ◽  
Urban Areas ◽  
Large Scale ◽  
Smart Cities ◽  
Urban Migration ◽  
Indian Government ◽  
Urban Remote Sensing ◽  
Urban Growth Scenarios

The study of urban areas and their development focuses on cities, their physical and demographic expansion and the tensions and impacts that go along with urban growth. Especially in developing countries and emerging national economies like India, consistent and up to date information or other planning relevant data all too often is not available. With its Smart Cities Mission, the Indian government places great importance on the future developments of Indian urban areas and pays tribute to the large-scale rural to urban migration. The potentials of urban remote sensing and its contribution to urban planning are discussed and related to the Indian Smart Cities Mission. A case study is presented showing urban remote sensing based information products for the city of Ahmedabad. Resulting urban growth scenarios are presented, hotspots identified and future action alternatives proposed.

scholarly journals Evaluation of Reinforcement Learning Traffic Signalling Strategies for Alternative Objectives: Implementation in the Network of Nicosia, Cyprus

2020 ◽  
Vol 21 (4) ◽  
pp. 295-302
Author(s):  
Haris Ballis ◽  
Loukas Dimitriou
Keyword(s):  
Reinforcement Learning ◽  
Environmental Sustainability ◽  
Urban Areas ◽  
Traffic Management ◽  
Large Scale ◽  
Smart Cities ◽  
Control Strategies ◽  
Urban Traffic ◽  
Signal Control ◽  
Urban Network

AbstractSmart Cities promise to their residents, quick journeys in a clean and sustainable environment. Despite, the benefits accrued by the introduction of traffic management solutions (e.g. improved travel times, maximisation of throughput, etc.), these solutions usually fall short on assessing the environmental impact around the implementation areas. However, environmental performance corresponds to a primary goal of contemporary mobility planning and therefore, solutions guaranteeing environmental sustainability are significant. This study presents an advanced Artificial Intelligence-based (AI) signal control framework, able to incorporate environmental considerations into the core of signal optimisation processes. More specifically, a highly flexible Reinforcement Learning (RL) algorithm has been developed towards the identification of efficient but-more importantly-environmentally friendly signal control strategies. The methodology is deployed on a large-scale micro-simulation environment able to realistically represent urban traffic conditions. Alternative signal control strategies are designed, applied, and evaluated against their achieved traffic efficiency and environmental footprint. Based on the results obtained from the application of the methodology on a core part of the road urban network of Nicosia, Cyprus the best strategy achieved a 4.8% increase of the network throughput, 17.7% decrease of the average queue length and a remarkable 34.2% decrease of delay while considerably reduced the CO emissions by 8.1%. The encouraging results showcase ability of RL-based traffic signal controlling to ensure improved air-quality conditions for the residents of dense urban areas.

A Study of Key Attributes Accountable for Development of a Smart City Projects & Factors Impacting its Implementation in India

2018 ◽  
Vol 6 (9) ◽  
pp. 19
Author(s):  
Shubhangi Sandeep Tambe
Keyword(s):  
Water Management ◽  
Smart City ◽  
Urban Areas ◽  
Large Scale ◽  
Smart Cities ◽  
Basic Question ◽  
Political Will ◽  
The World ◽  
The Government ◽  
Will Power

he concept of Smart Cities was first thought of by IBM in 2008 when world was facing its worst economic crisis. Then it was taken up by various countries around the world. The main objective here is to build and promote the cities which will provide the core infrastructure and provide the decent quality of life along with a clean and long-lasting environment which will be supported by smart technologies & solutions. Though smart city concepts are very new to India, where technology is mostly used in urban cities. So, in such a scenario one may ask a very basic question that “How a city can be made Smart?”. So, if we look around and see what are the things that some smart cities around the world are doing differently, then we may notice that they have addressed basic issues faced by any metropolitan city in a smarter way possible. For instance, we can see that the already developed smart city projects have addressed transportation, energy, crime, water management & other issues using current technologies & applications. If we leave aside the technology gap between rural & urban India, it is certain that Urban areas are already in need of Smart City Projects because of Population. But again, this needs a strong political will power to take quick decisions and aligned with technological advances such as E governance, online tendering of the government work which will be transparent and efficient. but often it is misunderstood that use of IT in administration and governance is the only meaning of Smart City Projects, but in fact if you are able to achieve all the issues such as administration, governance, transportation, water management, energy supplies, waste management, water treatments plants, meaningful use of public private partnerships in managing transportations and road constructions and evening installations of solar panels and LED bulbs across city. So basically, there are many factors contributing to create a smart city. The main factor which will drive this kind of ambitious projects are political will powers of government, without a political will power it is very difficult to complete the bigger projects. As there is lot on stake for such a large-scale project which will easily span over next decade.

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