Urbanization's rapid progress has modernized many people's lives but also engendered big issues, such as traffic congestion, energy consumption, and pollution. Urban computing aims to tackle these issues by using the data that has been generated in cities (e.g., traffic flow, human mobility, and geographical data). Urban computing connects urban sensing, data management, data analytics, and service providing into a recurrent process for an unobtrusive and continuous improvement of people's lives, city operation systems, and the environment. Urban computing is an interdisciplinary field where computer sciences meet conventional city-related fields, like transportation, civil engineering, environment, economy, ecology, and sociology in the context of urban spaces. This article first introduces the concept of urban computing, discussing its general framework and key challenges from the perspective of computer sciences. Second, we classify the applications of urban computing into seven categories, consisting of urban planning, transportation, the environment, energy, social, economy, and public safety and security, presenting representative scenarios in each category. Third, we summarize the typical technologies that are needed in urban computing into four folds, which are about urban sensing, urban data management, knowledge fusion across heterogeneous data, and urban data visualization. Finally, we give an outlook on the future of urban computing, suggesting a few research topics that are somehow missing in the community.

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Urban Computing: Concepts, Methodologies, and Applications

Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?

Crowdsourcing is traditionally defined as obtaining data or information by enlisting the services of a (potentially
large) number of people. However, due to recent innovations, this definition can now be expanded to include ‘and/or from a
range of public sensors, typically connected via the Internet.’ A large and increasing amount of data is now being obtained
from a huge variety of non-traditional sources – from smart phone sensors to amateur weather stations to canvassing members
of the public. Some disciplines (e.g. astrophysics, ecology) are already utilizing crowdsourcing techniques (e.g. citizen science
initiatives, web 2.0 technology, low-cost sensors), and while its value within the climate and atmospheric science disciplines
is still relatively unexplored, it is beginning to show promise. However, important questions remain; this paper introduces
and explores the wide-range of current and prospective methods to crowdsource atmospheric data, investigates the quality of
such data and examines its potential applications in the context of weather, climate and society. It is clear that crowdsourcing
is already a valuable tool for engaging the public, and if appropriate validation and quality control procedures are adopted
and implemented, it has much potential to provide a valuable source of high temporal and spatial resolution, real-time data,
especially in regions where few observations currently exist, thereby adding value to science, technology and society.

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Crowdsourcing for climate and atmospheric sciences: current status and future potential

The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems.

/pdf/a-survey-of-wireless-sensor-network-based-air-pollution-20phz05fru.pdf

A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems

Deriving high-resolution urban air pollution maps using mobile sensor nodes

Traditionally, pollution measurements are performed using expensive equipment at fixed locations or dedicated mobile equipment laboratories. This is a coarse-grained and expensive approach where the pollution measurements are few and far in-between. In this paper, we present a vehicular-based mobile approach for measuring fine-grained air quality in real-time. We propose two cost effective data farming models -- one that can be deployed on public transportation and the second a personal sensing device. We present preliminary prototypes and discuss implementation challenges and early experiments.

Real-time air quality monitoring through mobile sensing in metropolitan areas

Remote driving brings human operators with sophisticated perceptual and cognitive skills into an over-the-network control loop, with the hope of addressing the challenging aspects of vehicular autonomy based exclusively on artificial intelligence (AI). This paper studies the human behavior in a remote driving setup, i.e., how human remote drivers perform and assess their workload under the state-of-the-art network conditions. To explore this, we build a scaled remote driving prototype and conduct a controlled human study with varying network delays based on current commercial LTE network technology. The study demonstrates that remote driving over LTE is not immediately feasible, primarily caused by network delay variability rather than delay magnitude. In addition, our findings indicate that the negative effects of remote driving over LTE can be mitigated by a video frame arrangement strategy that regulates delay magnitude to achieve a smoother display.

Investigating Remote Driving over the LTE Network

A system and method for wireless device management in a telecommunications network (110) that includes a wireless device (120A-120Z) and a server (130A). An agent (225) executing on a wireless identity module (220) that is operatively connected to the wireless device (120A-120Z) communicates with a service manager executing on the serve (130A). The information communicated by the agent (225) may include the identity of the wireless device (120A-120Z), the network identity of the wireless identity module (220), the physical location of the wireless device (120A-120Z) in the telecommunications network (110), the signal strength and bit error rate of the primary communication channel used by the wireless device (120A-120Z) , and a list of features supported by the wireless device (120A-120Z). The service manager may then monitor the wireless device (120A-120Z), and may proactively query the wireless device (120A-120Z) via the agent (225) to ascertain the status of the wireless device (120A-120Z) and the quality of service provided to the wireless device (120A-120Z) by the telecommunications network (110).

System and method for over the air (ota) wireless device and network management

Systems and methods are described for securely downloading management client software onto a device from an embedded stub in the device. In one embodiment, the stub client is activated by a message with credentials from a management server. The stub client, after verification of the credentials, downloads and activates a full management client. The management client then participates in any authorized management session with the device management server. The messages are preferably encrypted using a key that is based on the credentials. The credentials may be specific to the device and to the service provider associated with the device.

System and method to securely load a management client from a stub client to facilitate remote device management

The present invention relates to a system and method of remote application management on wireless data terminals using a device management agent and dynamic link libraries provided by the application. Third party applications on a wireless device can communicate and be controlled by a remote management server via a management client plug-in interface.

Srinivas Devarakonda

Papers

Real-time air quality monitoring through mobile sensing in metropolitan areas

Investigating Remote Driving over the LTE Network

System and method for over the air (ota) wireless device and network management

System and method to securely load a management client from a stub client to facilitate remote device management

System and method to provide application management on wireless data terminals by means of device management agent and dynamic link libraries