9 May 2018 A scalable communication abstraction framework for internet of things applications using Raspberry Pi
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Abstract
The Internet of Things concept is described as a network of interconnected physical objects capable of gather, process, and communicate information about their environment, and potentially affect the physical world around them through their sensors, embedded processors, communication modules, and actuators, respectively. Such a network can provide vital information on events, processes, activities, and future projections about the state of a distributed system. In addition, it can give the devices inside the network awareness about their environment far beyond the range of their dedicated sensors through communication with other devices. In most cases, such network consists of devices with different processing and communication capacities and protocols, from a variety of hardware vendors. This paper introduces an abstracted messaging and commanding framework for smart objects, aimed towards making the network capable of including various communication standards. This issue is addressed by proposing a messaging structure based on JavaScript object notation (JSON) format so the new devices connecting to the network can introduce themselves to the central coordinator. The introduction includes a list of functionalities that the device is capable of, and the information it needs to carry out those tasks. This platform makes the network capable of incorporating different devices with various purposes and functions with ease and flexibility. Having a fast, reliable, and scalable communication scheme is critical for realization of a robust and flexible network.
Conference Presentation
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Behshad Mohebali, Behshad Mohebali, Amirhessam Tahmassebi, Amirhessam Tahmassebi, Amir H. Gandomi, Amir H. Gandomi, Anke Meyer-Baese, Anke Meyer-Baese, Simon Y. Foo, Simon Y. Foo, } "A scalable communication abstraction framework for internet of things applications using Raspberry Pi", Proc. SPIE 10652, Disruptive Technologies in Information Sciences, 1065205 (9 May 2018); doi: 10.1117/12.2306596; https://doi.org/10.1117/12.2306596
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