ABSTRACT
Due to the rapid development of the Internet of Things (IoT) and consequently, the availability of more and more IoT data sources, mechanisms for searching and integrating IoT data sources become essential to leverage all relevant data for improving processes and services. This paper presents the IoT search framework IoTCrawler. The IoTCrawler framework is not only another IoT framework, it is a system of systems which connects existing solutions to offer interoperability and to overcome data fragmentation. In addition to its domain-independent design, IoTCrawler features a layered approach, offering solutions for crawling, indexing and searching IoT data sources, while ensuring privacy and security, adaptivity and reliability. The concept is proven by addressing a list of requirements defined for searching the IoT and an extensive evaluation. In addition, real world use cases showcase the applicability of the framework and provide examples of how it can be instantiated for new scenarios.
ABSTRACT
Although current estimates depict steady growth in Internet of Things (IoT), many works portray an as yet immature technology in terms of security. Attacks using low performance devices, the application of new technologies and data analysis to infer private data, lack of development in some aspects of security offer a wide field for improvement. The advent of Semantic Technologies for IoT offers a new set of possibilities and challenges, like data markets, aggregators, processors and search engines, which rise the need for security. New regulations, such as GDPR , also call for novel approaches on data-security, covering personal data. In this work, we present DS4IoT, a data-security ontology for IoT, which covers the representation of data-security concepts with the novel approach of doing so from the perspective of data and introducing some new concepts such as regulations, certifications and provenance, to classical concepts such as access control methods and authentication mechanisms. In the process we followed ontological methodologies, as well as semantic web best practices, resulting in an ontology to serve as a common vocabulary for data annotation that not only distinguishes itself from previous works by its bottom-up approach, but covers new, current and interesting concepts of data-security, favouring implicit over explicit knowledge representation. Finally, this work is validated by proof of concept, by mapping the DS4IoT ontology to the NGSI-LD data model, in the frame of the IoTCrawler EU project.
ABSTRACT
OBJECTIVES: To assess the effects of an 8-week exercise training program with a special focus on light- to moderate-intensity resistance exercises (30-70% of one repetition maximum, 1RM) and a subsequent 4-week training cessation period (detraining) on muscle strength and functional capacity in participants aged 90 and older. DESIGN: Randomized controlled trial performed during March to September 2009. SETTING: Geriatric nursing home. PARTICIPANTS: Forty nonagenarians (90-97) were randomly assigned to an intervention or control group (16 women and 4 men per group). INTERVENTION: Eight-week muscle strength exercise intervention focused on lower limb strength exercises of light to moderate intensity. PRIMARY OUTCOME: 1RM leg press. SECONDARY OUTCOMES: handgrip strength, 8-m walk test, 4-step stairs test, Timed Up and Go test, and number of falls. RESULTS: A significant group by time interaction effect (P=.02) was observed only for the 1RM leg press. In the intervention group, 1RM leg press increased significantly with training by 10.6 kg [95% confidence interval (CI)=4.1-17.1 kg; P=.01]. Except for the mean group number of falls, which were 1.2 falls fewer per participant in the intervention group (95% CI=0.0-3.0; P=.03), no significant training effect on the secondary outcome measures was found. CONCLUSION: Exercise training, even of short duration and light to moderate intensity, can increase muscle strength while decreasing fall risk in nonagenarians.
