The Role of Advanced Sensing in Smart Cities

Abstract

In a world where resources are scarce and urban areas consume the vast majority of these resources, it is vital to make cities greener and more sustainable. Advanced systems to improve and automate processes within a city will play a leading role in smart cities. From smart design of buildings, which capture rain water for later use, to intelligent control systems, which can monitor infrastructures autonomously, the possible improvements enabled by sensing technologies are immense. Ubiquitous sensing poses numerous challenges, which are of a technological or social nature. This paper presents an overview of the state of the art with regards to sensing in smart cities. Topics include sensing applications in smart cities, sensing platforms and technical challenges associated with these technologies. In an effort to provide a holistic view of how sensing technologies play a role in smart cities, a range of applications and technical challenges associated with these applications are discussed. As some of these applications and technologies belong to different disciplines, the material presented in this paper attempts to bridge these to provide a broad overview, which can be of help to researchers and developers in understanding how advanced sensing can play a role in smart cities.

The real-time city? Big data and smart urbanism

“…Sensor networks consist of an array of very small, inexpensive sensors or actuators that can be embedded or placed on different structures to measure specific outputs such as levels of light, humidity, temperature, gas, electrical resistivity, acoustics, air pressure, movement, speed, and so on. Sensors can be passive and read by scanners, or can be active, broadcasting data at regular intervals over local or wide area networks, or they might have near field communication (NFC) capabilities that enables two-way communication (Hancke et al 2013). Sensors networks can be used to monitor the use and condition of public infrastructures, such as bridges, roads, buildings, and utility provision, as well as general environmental conditions within a city.…”

“…Automated forms of surveillance include: anonymous paper tickets being replaced with automatically trackable 'smart cards'; automatic number plate recognition (ANPR) systems that use digital cameras to scan license plates and pattern match the details to owner details and can be used to trace vehicles as they cross a city and provide inputs into intelligent transportation systems (ITS); automatic meter reading (AMR) that communicates utility usage without the need for manual reading and can do so on a continuous basis; and automated monitoring of public service provision, such as RFID chips attached to rubbish bins detecting whether they have been collected (Dodge and Kitchin 2007a;Hancke et al 2013). Sensor networks consist of an array of very small, inexpensive sensors or actuators that can be embedded or placed on different structures to measure specific outputs such as levels of light, humidity, temperature, gas, electrical resistivity, acoustics, air pressure, movement, speed, and so on.…”

“…On the one hand, the notion of a 'smart city' refers to the increasing extent to which urban places are composed of 'everyware' (Greenfield 2006); that is, pervasive and ubiquitous computing and digitally instrumented devices built into the very fabric of urban environments (e.g., fixed and wireless telecom networks, digitally controlled utility services and transport infrastructure, sensor and camera networks, building management systems, and so on) that are used to monitor, manage and regulate city flows and processes, often in real-time, and mobile computing (e.g., smart phones) used by many urban citizens to engage with and navigate the city which themselves produce data about their users (such as location and activity). Connecting up, integrating and analysing the information produced by these various forms of everyware, it is argued, provides a more cohesive and smart understanding of the city that enhances efficiency and sustainability (Hancke et al 2013, Townsend 2013) and provides rich seams of data that can used to better depict, model and predict urban processes and simulate the likely outcomes of future urban development (Schaffers et al 2011;Batty et al 2012). Everyware thus works to make a city knowable and controllable in new, more fine-grained, dynamic and interconnected ways that ''improve[s] the performance and delivery of public services while supporting access and participation'' (Allwinkle and Cruickshank 2011: 2).…”

The Light and Dark Side of The Black Box: Sensor-Based Technology in the Automotive Industry

“…Research has increasingly begun to study sensor-based technologies under the broad umbrella of the "Internet of things" (IoT): "a global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies" (ITU, n.d.). Sensor technologies are present in and affect a wide range of industries and societal contexts: examples include production process monitoring devices (Westergren & Holmstrom, 2012;Westergren & Wennerholm, 2013), healthcare (Zhang, Jiang, Wei, Marschollek, & Zhang, 2012;Pantelopolous & Bourbakis, 2010), urbanization and infrastructures (Hancke & Hancke, 2012;Su, Li, & Fu, 2011), agriculture and food production (RuizGarcia, Lunadei, Barreiro, & Robla, 2009), military and crime prevention (Durišić, Tafa, Dimić, & Volume 40…”

Opening up Smart Cities: Citizen-Centric Challenges and Opportunities from GIScience

“…Finally, GIScience's proposal of field as generic data type for big spatial data [105] is worth considering when dealing with issues of efficient data representation in a big data context. Sensors are crucial for intelligent systems like smart cities [110,111] and are well covered by the OGC Sensor Web Enablement (SWE) [112]. The OGC SWE standards suite specifies interfaces and metadata encodings to enable real-time integration of heterogeneous sensor networks [113].…”