Nowadays, numerous journals and conferences have published articles related to context-aware systems, indicating many researchers' interest. Therefore, the goal of this paper is to review the works that were published in journals, suggest a new classification framework of context-aware systems, and explore each feature of classification framework. This paper is based on a literature review of context-aware systems from 2000 to 2007 using a keyword index and article title search. The classification framework is developed based on the architecture of context-aware systems, which consists of the following five layers: concept and research layer, network layer, middleware layer, application layer and user infrastructure layer. The articles are categorized based on the classification framework. This paper allows researchers to extract several lessons learned that are important for the implementation of context-aware systems.

Context-aware systems

Detailed land use, which is difficult to obtain, is an integral part of urban planning. Currently, GPS traces of vehicles are becoming readily available. It conveys human mobility and activity information, which can be closely related to the land use of a region. This paper discusses the potential use of taxi traces for urban land-use classification, particularly for recognizing the social function of urban land by using one year's trace data from 4000 taxis. First, we found that pick-up/set-down dynamics, extracted from taxi traces, exhibited clear patterns corresponding to the land-use classes of these regions. Second, with six features designed to characterize the pick-up/set-down pattern, land-use classes of regions could be recognized. Classification results using the best combination of features achieved a recognition accuracy of 95%. Third, the classification results also highlighted regions that changed land-use class from one to another, and such land-use class transition dynamics of regions revealed unusual real-world social events. Moreover, the pick-up/set-down dynamics could further reflect to what extent each region is used as a certain class.

Land-Use Classification Using Taxi GPS Traces

This paper demonstrates a novel car-following model focused on passenger comfort, for example, a rapid deceleration will make passengers uncomfortable. The brake comfort model of car following was set up according to the relationship between vehicle deceleration and passenger comfort levels. The model calculates the controlled car's acceleration by measuring the distance between the controlled car and its preceding car, as well as the velocity of the controlled car. By controlling the car's acceleration, the model is able to keep riders feeling comfortable. The friction coefficient between the car and the road surface is also considered. Experiments show that the model is highly compatible with real cases.

A Smart Car Control Model for Brake Comfort Based on Car Following

Origin-destination(OD) flows reflect both human activity and urban dynamic in a city. However, our understanding about their patterns remains limited. In this paper, we study the GPS traces of taxis in a city with several millions people, China and find that there are significant patterns under the OD flows constructed from taxis' random motion. Our spatiotemporal analysis shows that those patterns have close relationship with the semantics of OD flows, hence we can mine the semantics of OD flows from raw GPS trace data. The approach we proposed offers a novel way to explore the human mobility and location characteristic.

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Mining the semantics of origin-destination flows using taxi traces

For shortcomings of current smart home system and power line carrier insufficient data transferring, an intelligent sensor networks system based on intelligent gateway is studied in this paper. Smart home system includes internal network, intelligent gateway, and external network. Multiple servers are designed in gateway, which start at the same time and receive various forms of data. Then data is processed for internal network format. External network includes several modes of communication such as TCP/IP, UDP, and pipe. Internal network includes ZigBee wireless and power line carrier (PLC) communication. Power line carrier protocol is improved, and it expands data transmission capacity to accommodate communication needs of modern family. Smart home system is designed as modules, such as intelligent gateway module, power line carrier communication module, ZigBee wireless communication modules, and appliance within electric equipment. Finally this system is physically designed and verified. The smart home system introduced in this paper has easily used and has strong compatibility.

https://journals.sagepub.com/doi/pdf/10.1155/2015/960173

An intelligent wireless sensor networks system with multiple servers communication

Compared with smart spaces addressed previously, the smart vehicle space is quite special. First, unlike room, it is a high mobile space. Second, it requires frequent information exchange with the outer environment; for instance, it may need local traffic information and other local services. The complex vehicle space needs a software infrastructure of high adaptation to meet the complex and easy variational situations. This paper proposes a semantic and adaptive middleware platform, i.e., ScudWare, for smart vehicle space. In ScudWare, techniques of multiagent, context-aware, and adaptive component management are smoothly synthesized. It consists of three key components, namely 1) semantic virtual agents; 2) a semantic context management service; and 3) an adaptive component management service. This enables entities in smart vehicle space to interact autonomously, provides semantic-integration context awareness, and supports component-based adaptability and scalability. A test bed of smart car space is built to evaluate the ScudWare, which demonstrates the effectiveness and efficiency of ScudWare.

ScudWare : A semantic and adaptive middleware platform for smart vehicle space

Compared with smart spaces addressed previously, the smart vehicle space is quite special. First, unlike room, it is a high mobile space. Second, it requires frequent information exchange with the outer environment; for instance, it may need local traffic information and other local services. The complex vehicle space needs a software infrastructure of high adaptation to meet the complex and easy variational situations. This paper proposes a semantic and adaptive middleware platform, i.e., ScudWare, for smart vehicle space. In ScudWare, techniques of multiagent, context-aware, and adaptive component management are smoothly synthesized. It consists of three key components, namely 1) semantic virtual agents; 2) a semantic context management service; and 3) an adaptive component management service. This enables entities in smart vehicle space to interact autonomously, provides semantic-integration context awareness, and supports component-based adaptability and scalability. A test bed of smart car space is built to evaluate the ScudWare, which demonstrates the effectiveness and efficiency of ScudWare

ScudWare: A Semantic and Adaptive Middleware Platform for Smart Vehicle Space

The need for component-based middleware adaptation is growing, due to the complexities of increasing prevalence of ubiquitous computing. Software middleware must dynamically adapt to changing environments and conditions. Dynamic adaptation must be performed reliably and correctly. The focus of this paper regards an approach to formally specifying adaptation semantics for scudware middleware in smart vehicle space. The contribution of our work is twofold. First, a context-aware adaptation temporal logic is put forward to specify component-based dynamic adaptation semantics. Second, we propose three adaptation specification composition operations to generate the whole adaptation specification of adaptive middleware. In addition, this adaptation specification is applied into a mobile music system in smart vehicle space.

Minde Zhao

Papers

ScudWare : A semantic and adaptive middleware platform for smart vehicle space

ScudWare: A Semantic and Adaptive Middleware Platform for Smart Vehicle Space

Weaving adaptation semantic specification into scudware middleware for ubiquitous computing