RFL-IoT: An IoT Reconfiguration Framework Applied Fuzzy Logic for Context Management

Nguyen-Anh, Tuan; Le‐Trung, Quan

doi:10.1109/rivf.2019.8713619

Cited by 7 publications

(2 citation statements)

References 11 publications

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“…Nguyen-ANH and Le-Trung [9] proposed RFL-IoT, a framework for reconfiguring IoT systems with focus on intelligent context management based on fuzzy logic. The RFL-IoT architecture is structured in three layers, (i) physical, (ii) middleware, and (iii) application.…”

Section: Related Workmentioning

confidence: 99%

“…The use of an IoT middleware platform is important because it abstracts away the specificities of the integrated physical devices, provides the system with greater interoperability regarding other solutions, and contributes to ease application development, but most of the works neglects this issue. The Malche and Maheshwary [6] and Nguyen-ANH and Le-Trung's [9] works are the only ones that use a middleware platform, but the former does not use a platform that allows customizing the solution, whereas the latter uses a platform that was proposed in the authors' previous works. Regarding the other issues, the proposals of Havard et al [5] and Medina and Manera [7] do not have a graphical user interface, thus hampering setup and monitoring by an end-user.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Energy Efficiency in Smart Buildings: An IoT-Based Air Conditioning Control System

Rocha

Dantas

Santos

et al. 2020

IFIP Advances in Information and Communication Technology

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The misuse of high-power electrical appliances such as air conditioners in both commercial and residential buildings has contributed to the inefficient use of energy resources. To face this scenario, smart buildings focus on minimizing energy consumption while improving the experience and productivity of users in these environments. Aiming at optimizing the use of air conditioners towards energy efficiency, this work presents Smart Place, an Internet of Things (IoT)-based ambient management system for automatically controlling those equipments. In this system, sensors and video cameras collect data regarding temperature, humidity, and presence of people in monitored spaces. These data are parameters for performing interventions on air conditioners in order to avoid keeping them turned on when the environment is not being used.The system also provides a Web interface for managing devices and monitored environments as well as it is integrated to the FIWARE platform as underlying middleware. This paper describes Smart Place, its architecture, and its operation at the Federal University of Rio Grande do Norte (UFRN), Natal, Brazil. The paper also discusses the benefits resulted from the automatic intervention performed by Smart Place, which has been able to save 61.8% in energy consumption compared to the traditional manual control in a set of classrooms.

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Section: Related Workmentioning

confidence: 99%