EPOPTIS: A Monitoring-as-a-Service Platform for Internet-of-Things Applications.

The technology landscape has been dynamically reshaped by the rapid growth of the Internet of Things, introducing an era where everyday objects, equipped with smart sensors and connectivity, seamlessly interact to create intelligent ecosystems. IoT devices are highly heterogeneous in terms of software and hardware, and many of them are severely constrained. This heterogeneity and potentially constrained nature creates new challenges in terms of security, privacy, and data management. This work proposes a Monitoring-as-a-Service platform for both monitoring and management purposes, offering a comprehensive solution for collecting, storing, and processing monitoring data from heterogeneous IoT networks for the support of diverse IoT-based applications. To ensure a flexible and scalable solution, we leverage the FIWARE open-source framework, also incorporating blockchain and smart contract technologies to establish a robust integrity verification mechanism for aggregated monitoring and management data. Additionally, we apply automated workflows to filter and label the collected data systematically. Moreover, we provide thorough evaluation results in terms of CPU and RAM utilization and average service latency.

Quantifying the Computational Efficiency of Compressive Sensing in Smart Water Network Infrastructures.

Monitoring contemporary water distribution networks (WDN) relies increasingly on smart metering technologies and wireless sensor network infrastructures. Smart meters and sensor nodes are deployed to capture and transfer information from the WDN to a control center for further analysis. Due to difficulties in accessing the water assets, many water utility companies employ battery-powered nodes, which restricts the use of high sampling rates, thus limiting the knowledge we can extract from the recorder data. To mitigate this issue, compressive sensing (CS) has been introduced as a powerful framework for reducing dramatically the required bandwidth and storage resources, without diminishing the meaningful information content. Despite its well-established and mathematically rigorous foundations, most of the focus is given on the algorithmic perspective, while the real benefits of CS in practical scenarios are still underexplored. To address this problem, this work investigates the advantages of a CS-based implementation on real sensing devices utilized in smart water networks, in terms of execution speedup and reduced ener experimental evaluation revealed that a CS-based scheme can reduce compression execution times around 50 % , while achieving significant energy savings compared to lossless compression, by selecting a high compression ratio, without compromising reconstruction fidelity. Most importantly, the above significant savings are achieved by simultaneously enabling a weak encryption of the recorded data without the need for additional encryption hardware or software components.

Federation of Internet of Things Testbeds for the Realization of a Semantically-Enabled Multi-Domain Data Marketplace.

The Internet of Things (IoT) concept has attracted a lot of attention from the research and innovation community for a number of years already. One of the key drivers for this hype towards the IoT is its applicability to a plethora of different application domains. However, infrastructures enabling experimental assessment of IoT solutions are scarce. Being able to test and assess the behavior and the performance of any piece of technology (i.e., protocol, algorithm, application, service, etc.) under real-world circumstances is of utmost importance to increase the acceptance and reduce the time to market of these innovative developments. This paper describes the federation of eleven IoT deployments from heterogeneous application domains (e.g., smart cities, maritime, smart building, crowd-sensing, smart grid, etc.) with over 10,000 IoT devices overall which produce hundreds of thousands of observations per day. The paper summarizes the resources that are made available through a cloud-based platform. The main contributions from this paper are twofold. In the one hand, the insightful summary of the federated data resources are relevant to the experimenters that might be seeking for an experimental infrastructure to assess their innovations. On the other hand, the identification of the challenges met during the testbed integration process, as well as the mitigation strategies that have been implemented to face them, are of interest for testbed providers that can be considering to join the federation.

Blue CrO5 assay: a novel spectrophotometric method for the evaluation of the antioxidant and oxidant capacity of various biological substances.

Oxidative stress plays a pivotal role in the ageing process and in the pathogenesis of numerable diseases. The quantification of the phenomenon is of paramount importance. In the present study, we introduce a novel and simple assay, the Blue CrO(5) assay, for the evaluation of the oxidant and antioxidant capacity of various biological samples and known antioxidants. Chromium peroxide (CrO(5)) is produced by ammonium dichromate in an acidic environment in the presence of H(2)O(2). It is a deep blue potent oxidant compound, miscible and relatively stable in polar organic solvents, that can be easily measured by spectrophotometry. Its reduction by known antioxidants, both water- and lipid-soluble (ascorbate and alpha-tocopherol, respectively, in this study), detected spectrophotometrically as a decrease in the absorption and depicted in EPR spectra, can act as a measure of the antioxidant capacity of a certain compound. The assay displays significant sensitivity, stability, linearity, specificity and repeatability.