Towards Ontology-Based Requirements Engineering for IoT-Supported Well-Being, Aging and Health

Ontologies serve as a one of the formal means to represent and model knowledge in computer science, electrical engineering, system engineering and other related disciplines. Ontologies within requirements engineering may be used for formal representation of system requirements. In the Internet of Things, ontologies may be used to represent sensor knowledge and describe acquired data semantics. Designing an ontology comprehensive enough with an appropriate level of knowledge expressiveness, serving multiple purposes, from system requirements specifications to modeling knowledge based on data from IoT sensors, is one of the great challenges. This paper proposes an approach towards ontology-based requirements engineering for well-being, aging and health supported by the Internet of Things. Such an ontology design does not aim at creating a new ontology, but extending the appropriate one already existing, SAREF4EHAW, in order align with the well-being, aging and health concepts and structure the knowledge within the domain. Other contributions include a conceptual formulation for Well-Being, Aging and Health and a related taxonomy, as well as a concept of One Well-Being, Aging and Health. New attributes and relations have been proposed for the new ontology extension, along with the updated list of use cases and particular ontological requirements not covered by the original ontology. Future work envisions full specification of the new ontology extension, as well as structuring system requirements and sensor measurement parameters to follow description logic.Comment: 10 pages, 2 figures, 2 table

Hardware and Software Solutions

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IoT Wallet:Machine Learning-based Sensor Portfolio Application

In this paper an application for building sensor wallet is presented. Currently, given system collects sensor data from The Things Network (TTN) cloud system, stores the data into the Influx database and presents the processed data to the user dashboard. Based on the type of the user, data can be viewed-only, controlled or the top user can register the sensor to the system. Moreover, the system can notify users based on the rules that can be adjusted through the user interface. The special feature of the system is the machine learning service that can be used in various scenarios and is presented throughout the case study that gives a novel approach to estimate soil moisture from the signal strength of a given underground LoRa beacon node.Comment: 5 pages, 6 figures, in proceedings of the 5th International Conference on Smart and Sustainable Technologies 2020, SpliTech202

A Novel IoT-aware Smart Parking System based on the integration of RFID and WSN technologies

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Analysis of SDR-Based RFID reader: Filling Out the Gaps

RFID reader implemented on a Software Defined Radio (SDR) platform is a desired environment for the ease experimentation and verification of varoius research contributions. It offers several features such as studying separately any part of a RFID reader for further modification and improvements. In the recent years, fruitful attempts for making the basement that facilitates the future researches were published. To begin from the sketch and start prototyping on the given platform, a big variety of information that has to be organized and learned due to comprehensive and complex topic mostly of interdisciplinary nature. On the other side, finding details are important for perceiving the whole functionality of the system and making the required changes. Tutorial-based description in one unique paper is hard to accomplish due to the volume of details. In this paper a heuristic method for filling out all the important and missing parts of the puzzle is given. Moreover, this paper gives a simplified but comprehensive view about making an RFID radio through SDR including their flow graphs, code blocks, and other important procedures with focus on practical and useful details crucial for fast implementation of any new research in the given platform

A Smart Remote Elderly Monitoring System based on IoT Technologies

The aging population phenomenon is more and more increasing. In this context, the elderly’s behavioral analysis through the Internet of Things technologies can help to prevent Mild Cognitive Impairment and frailty problems. In particular, since movements and body motility are good indicators of behavioral changes, this work aims to define a reliable system for controlling the position and the body motility of the elderly in unobtrusive, low-cost and low-power way. The system represents the basis of a complete architecture for behavioral analysis and risk detection developed within the City4Age project, funded by the Horizon 2020 Programme of the European Commission