Intelligent Tools to Monitor, Control and Predict Wastewater Reclamation and Reuse.

Contemporary wastewater reclamation units entail several diverse treatment and extraction processes, with a multitude of monitored quality characteristics, controlled by a variety of key operational parameters directly affecting the efficiency of treatment. The conventional optimization of this highly complex system is time- and energy- consuming, frequently relying on intuitive decision making by operators, and does not predict or forecast efficiency changes and system maintenance. In this paper, we introduce intelligent solutions to enhance the operational control of the unit with minimal human intervention and to develop an AI-powered DSS that is installed atop the sensors of a water treatment module. The DSS uses an expert model, both to assess the quality of water and to offer suggestions based on current values and future trends. More specifically, the quality of the produced water was successfully visualized, assessed and rated, based on a set of input operational variables (pH, TOC for this case), while future values of monitored sensors were forecasted. Additionally, monitoring services of the DSS were able to identify unexpected events and to generate alerts in the case of observed violation of operational limits, as well as to implement changes (automatic responses) to operational parameters so as to reestablish normal operating conditions and to avoid such events in the future. Up to now, the DSS suggestion and forecasting services have proven to be adequately accurate. Though data are still being collected from early adopters, the solution is expected to provide a complete water treatment solution that can be adopted by a vast range of parties.

Incorporating patient concerns into design requirements for IoMT-based systems: The fall detection case study.

Internet of Medical Things (IoMT) systems are envisioned to provide high-quality healthcare services to patients in the comfort of their home, utilizing cutting-edge Internet of Things (IoT) technologies and medical sensors. Patient comfort and willingness to participate in such efforts is a prominent factor for their adoption. As IoT technology has provided solutions for all technical issues, patient concerns are those that seem to restrict their wider adoption. To enhance patient awareness of the system properties and enhance their willingness to adopt IoMT solutions, this paper presents a novel methodology to integrate patient concerns in the design requirements of such systems. It comprises a number of straightforward steps that an IoMT designer can follow, starting from identifying patient concerns, incorporating them in system design requirements as criticalities, proceeding to system implementation and testing, and finally, verifying that it fulfills the concerns of the patients. To showcase the effectiveness of the proposed methodology, the paper applies it in the design and implementation of a fall detection system for elderly patients remotely monitored in their homes.

The use of a non-lethal tool for evaluating toxicological hazard of organochlorine contaminants in Mediterranean cetaceans: new data 10 years after the first paper published in MPB.

In the Mediterranean Sea, top predators, and particularly cetacean odontocetes, accumulate high concentrations of organochlorine contaminants and toxic metals, incurring high toxicological risk. In this paper we investigate the use of the skin biopsies as a non-lethal tool for evaluating toxicological hazard of organochlorines in Mediterranean cetaceans, presenting new data 10 years after the paper published by Fossi and co-workers [Mar. Poll. Bull. 24 (9) (1992) 459] in which this new methodology was first presented. Some organochlorine compounds, now with worldwide distribution, are known as endocrine disrupting chemicals (EDCs). Here the unexplored hypothesis that Mediterranean cetaceans are potentially at risk due to organochlorines with endocrine disrupting capacity is investigated. High concentrations of DDT metabolites and PCB congeners (known as EDCs) were found in the different Mediterranean species (Stenella coeruleoalba, Delphinus delphis, Tursiops truncatus and Balaenoptera physalus). In this paper we also propose benzo(a)pyrene monooxygenase (BPMO) activity in marine mammal skin biopsies (non-lethal biomarker) as a potential indicator of exposure to organochlorines, with special reference to the compounds with endocrine disrupting capacity. A statistically significant correlation was found between BPMO activity and organochlorine levels (DDTs, pp(')DDT, op(')DDT, PCBs and PCB99) in skin biopsies of males of B. physalus. Moreover a statistical correlation was also found between BPMO activity and DDT levels in skin biopsies of the endangered Mediterranean population of D. delphis. These results suggest that BPMO induction may be an early sign of exposure to organochlorine EDCs and can be used for periodic monitoring of Mediterranean marine mammal toxicological status.