Internet of Things for Sustainability: Perspectives in Privacy, Cybersecurity, and Future Trends

In the sustainability IoT, the cybersecurity risks to things, sensors, and monitoring systems are distinct from the conventional networking systems in many aspects. The interaction of sustainability IoT with the physical world phenomena (e.g., weather, climate, water, and oceans) is mostly not found in the modern information technology systems. Accordingly, actuation, the ability of these devices to make changes in real world based on sensing and monitoring, requires special consideration in terms of privacy and security. Moreover, the energy efficiency, safety, power, performance requirements of these device distinguish them from conventional computers systems. In this chapter, the cybersecurity approaches towards sustainability IoT are discussed in detail. The sustainability IoT risk categorization, risk mitigation goals, and implementation aspects are analyzed. The openness paradox and data dichotomy between privacy and sharing is analyzed. Accordingly, the IoT technology and security standard developments activities are highlighted. The perspectives on opportunities and challenges in IoT for sustainability are given. Finally, the chapter concludes with a discussion of sustainability IoT cybersecurity case studies

On the cross-layer interactions between congestion and contention in wireless sensor and actor networks

Wireless Sensor and Actor Networks (WSAN) are composed of large number of sensor nodes collaboratively observing a physical phenomenon and relatively smaller number of actor nodes, which act upon the sensed phenomenon. Due to the limited capacity of shared wireless medium and memory restrictions of the sensor nodes, channel contention and network congestion can be experienced during the operation of the network. In fact, the multi-hop nature of WSAN entangles the level of local contention and the experienced network congestion. Therefore, the unique characteristics of WSAN necessitate a comprehensive analysis of the network congestion and contention under various network conditions. In this paper, we comprehensively investigate the interactions between contention resolution and congestion control mechanisms as well as the physical layer effects in WSAN. An extensive set of simulations are performed in order to quantify the impacts of several network parameters on the overall network performance. The results of our analysis reveal that the interdependency between network parameters call for adaptive cross-layer mechanisms for efficient data delivery in WSAN

Clinical and Prognostic Significance of Heart Rate Variability in Pulmonary Hypertension

34th Annual Meeting and Scientific Sessions of the International-Society-for-Heart-and-Lung-Transplantation -- APR 10-13, 2014 -- San Diego, CAWOS: 000333866700620Int Soc Heart & Lung Transplanta

Data Aware Communication for Energy Harvesting Sensor Networks

Part 3: Energy EfficiencyInternational audienceWe propose a Data Aware Communication Technique (DACT) that reduces energy consumption in Energy Harvesting Wireless Sensor Networks (EH-WSN). DACT takes advantage of the data correlation present in household EH-WSN applications to reduce communication overhead. It adapts its functionality according to correlations in data communicated over the EH-WSN and operates independently from spatial and temporal correlations without requiring location information. Our results show that DACT improves communication efficiency of sensor nodes and can help reduce idle energy consumption in an average-size home by up to 90 % as compared to spatial/temporal correlation-based communication techniques

Spectroscopy

Malassezia species which are lipophilic exobasidiomycetes fungi, have been accepted as members of normal cutaneous flora as well as causative agent of certain skin diseases. In routine microbiology laboratory, species identification based on phenotypic characters may not yield identical results with taxonomic studies. Lipophilic and lipid-dependent Malassezia yeasts require lipid-enriched complex media. For this reason, Fourier transform infrared (FT-IR) spectroscopy analysis focused on lipid window may be useful for identification of Malassezia species. In this study, 10 different standard Malassezia species (M.dermatis CBS 9145, M.furfur CBS 7019, M.japonica CBS 9432, M.globosa CBS 7966, M.nana CBS 9561, M.obtusa CBS 7876, M.pachydermatis CBS 1879, M.slooffiae CBS 7956, M.sympodialis CBS 7222 and M.yamatoensis CBS 9725) which are human pathogens, have been analyzed by FT-IR spectroscopy following standard cultivation onto modified Dixon agar medium. Results showed that two main groups (M1; M.globosa, Robtusa, M.sympodialis, M.dermatis, M.pachydermatis vs, M2; M.furfur, M.japonica, M.nana, M.slooffiae, M.yamatoensis) were discriminated by whole spectra analysis. M.obtusa in M1 by 1686-1606 cm(-1) wavenumber ranges and M.japonicum in M2 by 2993-2812 cm(-1) wavenumber ranges were identified with low level discrimination power. Discriminatory areas for species differentiation of M1 members as M.sympodialis, M.globosa and M.pachydermatis and M2 members as M.furfur and M.yamatoensis could not be identified. Several spectral windows analysis results revealed that FT-IR spectroscopy was not sufficient for species identification of culture grown Malassezia species