| Title | Ambient Intelligence in Smart City Environments: Topologies and Information Architectures |
|---|---|
| ID_Doc | 36575 |
| Authors | Bwalya, KJ |
| Title | Ambient Intelligence in Smart City Environments: Topologies and Information Architectures |
| Year | 2019 |
| Published | |
| Abstract | Many cities around the world have embarked on ambitious programmes towards creating Smart Cities where information, diverse digital opportunities, and collective intelligence can be harnessed ubiquitously. Smart Cities are conceptualized using citywide smart and intelligent architectures informed by the context in which they are implemented. These architectures make it possible to access information and intelligence anywhere and at any time. Information processing and computing is embedded within the urban infrastructures to a point where immovable city entities such as traffic lights are more intelligent to make real-time decisions based on the happenings in the environment in which they are deployed. Advanced development of ambient computing within the realm of Smart Cities will further culminate into possibilities such as vehicle-to-vehicle communication (V2V) and mobile-to-mobile (M2M) communication. Using extensive and critical literature review, this chapter specifically focusses on the design of information architectures that will ultimately support the enshrining of spatial intelligence within Smart City environments hinged on the internet of things (IoT) and cloud/fog computing. The chapter presents latest trends in the research and practice of ambient intelligence (AmI) linked to the realization of the key principles of Smart Cities from the information topology and architecture point of view. A conceptual ambient intelligence architecture that highlights the building blocks of any ambient intelligence architecture as deployed in Smart City environments is also proposed. The proposed conceptual architecture can be used as a blueprint in the design of ambient intelligence topologies and architectures in different contextual settings. |
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