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iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings
Providing personalized energy-use information to individual occupants enables the adoption of energy-aware behaviors in commercial buildings. However, the implementation of individualized feedback still remains challenging due to the difficulties in collecting personalized data, tracking personal behaviors, and delivering personalized tailored information to individual occupants. Nowadays, the Internet of Things (IoT) technologies are used in a variety of applications including real-time monitoring, control, and decision-making due to the flexibility of these technologies for fusing different data streams. In this paper, we propose a novel IoT-based smartphone energy assistant (iSEA) framework which prompts energy-aware behaviors in commercial buildings. iSEA tracks individual occupants through tracking their smartphones, uses a deep learning approach to identify their energy usage, and delivers personalized tailored feedback to impact their usage. iSEA particularly uses an energy-use efficiency index (EEI) to understand behaviors and categorize them into efficient and inefficient behaviors. The iSEA architecture includes four layers: physical, cloud, service, and communication. The results of implementing iSEA in a commercial building with ten occupants over a twelve-week duration demonstrate the validity of this approach in enhancing individualized energy-use behaviors. An average of 34% energy savings was measured by tracking occupants’ EEI by the end of the experimental period. In addition, the results demonstrate that commercial building occupants often ignore controlling over lighting systems at their departure events that leads to wasting energy during non-working hours. By utilizing the existing IoT devices in commercial buildings, iSEA significantly contributes to support research efforts into sensing and enhancing energy-aware behaviors at minimal costs
Evaluating of the disinfection and water quality effects on UV application in the primary stage of water treatment
Background: Irradiation of water by UV has been considered as an attractive alternative for disinfection because its low-impact, pathogen killing capacity shows tremendous promise for meeting today's drinking water regulatory requirements. This study has been performed with the objective of utilizing medium pressure lamp in the preliminary stage of municipal water treatment, namely prior to water clarification and filtration. Methods: Raw water samples were irradiated for 30 s in a lab-scale closed reactor. Disinfection results showed nearly 2 log reduction in HPC for all the samples without formation of nitrite in excess of its MCL. As in a few previous works the formation of nitrite as an objectionable DBP had been reported, this study was extended by preparing synthetic water samples having different amounts of nitrate and turbidities. Results: As far as the initial nitrate concentration dose not exceed 10 mg/L N-NO3, there would be no risk of nitrite increasing in excess of the MCL. Conclusion: Meeting the goal of at least 90 % disinfection for water samples with turbidity levels of as high as 750 NTU is possible by utilizing medium- pressure UV lamp
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