Smart Cities via Data Aggregation

Abstract

Cities have an ever increasing wealth of sensing capabilities, recently including also Internet of Things (IoT) systems. However, to fully exploit such sensing capabilities with the aim of offering effective citysensing-driven applications still presents certain obstacles. Indeed, at present, the main limitation in this respect consists of the vast majority of data sources being served on a "best effort" basis. To overcome this limitation, we propose a "resilient and adaptive IoT and social sensing platform". Resilience guarantees the accurate, timely and dependable delivery of the complete/related data required by smart-city applications, while adaptability is introduced to ensure optimal handling of the changing requirements during application provision. The associated middleware consists of two main sets of functionalities: (a) Formulation of sensing requests: selection and discovery of the appropriate data sources; and (b) Establishment and control of the necessary resources (e.g., smart objects, networks, computing/storage points) on the delivery path from sensing devices to the requesting applications. The middleware has the intrinsic feature of producing sensing information at a certain level of detail (geographical scope/timeliness/accuracy/completeness/dependability) as requested by the applications in a given domain. The middleware is assessed and validated at a proof-of-concept level through innovative, dependable and real-time applications expected to be highly reproducible across different cities.

Sii-Mobility: an IOT/IOE Architecture to Enhance Smart City Services of Mobility and Transportation

“…• provide a programmable environment to define algorithms for machine learning and data analysis, able to extract characteristics from the collected data (aggregation of data) [13] and elaborated them in order to implement predictive capabilities for guessing their future evolution: smart parking, predictions on traffic flow, traffic flow reconstruction; • enable visual presentations of data via a set of dashboards composed by widget components that a City Operator can manage graphically; these widgets have to be manageable/configurable by a person that may not know deeply the technicisms behind the IoT infrastructure.…”

“…It (4,5) saves locally the status "Prohibited Access" for both the Smart Gates and it (6, 12) sends the "Prohibited Access" signal to both Smart Gates and waits to receive from them an ACK message with the status they intend to change: in this case a "Prohibited Access" ACK must return (7,13). Once this ACK has been received, the system (8,14) responds with a second ACK containing the status "Prohibited Access".…”

Combined use of lifecycle management and IoT in smart cities

“…O. Isaksson et al [17] also see "service" as part of the wider concept of "product". Hence, the same definition of "product" can be extended to smart city as a composition of smart objects, smart systems, and smart services that focus on problems and issues that arise in service sectors, like transport, logistics, energy, waste management [18] [19]. Accordingly, A. Hefnawy et al [6] [8] have used this analogy to propose lifecycle management approach to be used in the smart city context to manage data, versions, variants and business processes associated with heterogeneous, uniquely identified connected objects.…”

Lifecycle Management in the Smart City Context: Smart Parking Use-Case

“…Smart city is a composition of smart objects, smart systems, and smart services that focus on problems and issues that arise in service sectors, like transport, logistics, energy, waste management [18] [19]. Yet, smart city as a complete ecosystem goes beyond conventional product systems, service systems or PSS [20] [21].…”

“…The proposed system features data exchange between waste management, surveillance/ monitoring and transportation/ routing smart systems. Another example, from [19], a CCTV camera video stream to feed to a video processing algorithm that extracts information such as numbers of cars/people/objects in a given street. Authors propose a middleware layer for selection and discovery of the appropriate data sources.…”