Home Chimney Pinwheels (HCP) as Steh and Remote Monitoring for Smart Building IoT and WSN Applications.

Smart, and ultra-low energy consuming Internet of Things (IoTs), wireless sensor networks (WSN), and autonomous devices are being deployed to smart buildings and cities, which require continuous power supply, whereas battery usage has accompanying environmental problems, coupled with additional maintenance cost. We present Home Chimney Pinwheels (HCP) as the Smart Turbine Energy Harvester (STEH) for wind; and Cloud-based remote monitoring of its output data. The HCP commonly serves as an external cap to home chimney exhaust outlets; they have very low inertia to wind; and are available on the rooftops of some buildings. Here, an electromagnetic converter adapted from a brushless DC motor was mechanically fastened to the circular base of an 18-blade HCP. In simulated wind, and rooftop experiments, an output voltage of 0.3 V to 16 V was realised for a wind speed between 0.6 to 16 km/h. This is sufficient to operate low-power IoT devices deployed around a smart city. The harvester was connected to a power management unit and its output data was remotely monitored via the IoT analytic Cloud platform "ThingSpeak" by means of LoRa transceivers, serving as sensors; while also obtaining supply from the harvester. The HCP can be a battery-less "stand-alone" low-cost STEH, with no grid connection, and can be installed as attachments to IoT or wireless sensors nodes in smart buildings and cities.

A Novel Social Distancing Approach for Limiting the Number of Vehicles in Smart Buildings Using LiFi Hybrid-Network.

The coronavirus (COVID-19) has arisen as one of the most severe problems due to its ongoing mutations as well as the absence of a suitable cure for this virus. The virus primarily spreads and replicates itself throughout huge groups of individuals through daily touch, which regretfully can happen in several unanticipated way. As a result, the sole viable attempts to constrain the spread of this new virus are to preserve social distance, perform contact tracing, utilize suitable safety gear, and enforce quarantine measures. In order to control the virus's proliferation, scientists and officials are considering using several social distancing models to detect possible diseased individuals as well as extremely risky areas to sustain separation and lockdown procedures. However, models and systems in the existing studies heavily depend on the human factor only and reveal serious privacy vulnerabilities. In addition, no social distancing model/technique was found for monitoring, tracking, and scheduling vehicles for smart buildings as a social distancing approach so far. In this study, a new system design that performs real-time monitoring, tracking, and scheduling of vehicles for smart buildings is proposed for the first time named the social distancing approach for limiting the number of vehicles (SDA-LNV). The proposed model employs LiFi technology as a wireless transmission medium for the first time in the social distance (SD) approach. The proposed work is considered as Vehicle-to-infrastructure (V2I) communication. It might aid authorities in counting the volume of likely affected people. In addition, the proposed system design is expected to help reduce the infection rate inside buildings in areas where traditional social distancing techniques are not used or applicable.

AkiKomi: Design and Implementation of a Mobile App System for Real-time Room Occupancy Estimation

During the COVID-19 pandemic some organizations chose to restrict the number of people permitted to occupy a room simultaneously. People in these organizations often had difficulty finding an available room. In this study we designed, implemented, and evaluated a mobile app-based real-time room occupancy estimation system named AkiKomi. The system comprises a set of distributed Grid-EYE sensors, a Message Queueing Telemetry Transport broker hosted in the Amazon Web Service cloud platform, and a mobile app that runs on users' mobile devices. We conducted a pilot usability test using the System Usability Scale questionnaire. The results showed that the system achieved a total score of 73.4, above the cut-off threshold of good usability. © 2022 IEEE.

The future of work, workplaces and smart buildings

This paper presents a discussion on how smart buildings and technologies currently and will continue to contribute to the future of work and workplaces. In the aftermath of the COVID-19 pandemic, a hybrid way of working has emerged and physical office spaces are becoming more a space for collaboration, innovation and interactions, which can be facilitated by the use of smart technologies. An analysis of the 15 highest-scoring smart buildings through the Smart Building Certification process highlights key trends in the smartest buildings as they contribute to the future of work and a hybrid way of working: increased flexibility, emphasis on user experience including indoor environmental quality and safety, and an overall drive towards sustainability. The shift towards smarter buildings also offers an opportunity to study the impacts of smart technologies on key performance aspects of the buildings and the building occupants. © 2022 ACM.

The Prototype of Healthy Smart Building Based on Google Assistant

Coronaviruses are a group of viruses from the subfamily Orthocronavirinae in the Coronaviridae family and the order Nidovirales. In general, the transmission of this virus occurs through droplets or body fluids splashed on someone or objects around them within 1-2 meters' distance away through coughing and sneezing. Office buildings, cafes, and shopping areas are one of the clusters for spreading the coronavirus because the following places lack awareness of health protocols. This research will create a healthy and Smart Building system where this system consists of two devices from the following problems. The first device is a health procedures checker system where using an ultrasonic sensor as an automatic switch can provide a hand sanitizer as the first step to kill viruses. The GY609 sensor is used, which can measure the temperature of visitors without touching it. The second system is the Smart Switch;the doors and lights can control using voice using google assistant to minimize the doorknob's touch or the light switch. The healthy and Smart building test results are for the intelligent, healthy procedures system, 3-7 cm is the optimal distance from the hand to the sensor, 5cm is the distance from the hand to the temperature sensor, and the motor working time is 1 second. For the Smart switches, the recommended network system is 3G, 4G, or Wi-Fi to avoid excessive delays. © 2022 IEEE.

Energy Management in an Agile Workspace using AI-driven Forecasting and Anomaly Detection

Smart building technologies transform buildings into agile, sustainable, and health-conscious ecosystems by leveraging IoT platforms. In this regard, we have developed a Persuasive Energy Conscious Network (PECN) at the University of Glasgow to understand the user-centric energy consumption patterns in an agile workspace. PECN consists of desk-level energy monitoring sensors that enable us to develop user-centric models that can be exploited to characterize the normal energy usage behavior of an office occupant. In this study, we make use of staked long short-term memory (LSTM) to forecast future energy demands. Moreover, we employed statistical techniques to automate the detection of anomalous power consumption patterns. Our experimental results indicate that post-anomaly resolution leads to 6.37% improvement in the forecasting accuracy. © 2022 IEEE.

Understanding Sustainable Energy in the Context of Smart Cities: A PRISMA Review

In the context of smart cities, sustainability is an essential dimension. One of the ways to achieve sustainability and reduce the emission of greenhouse gases in smart cities is through the promotion of sustainable energy. The demand for affordable and reliable electrical energy requires different energy sources, where the cost of production often outweighs the environmental factor. This paper aims to investigate the ways smart cities promote sustainability in the electricity sector. For this, a systematic literature review using the PRISMA protocol was employed as the methodological approach. In this review, 154 journal articles were thoroughly analyzed. The results were grouped according to the themes and categorized into energy efficiency, renewable energies, and energy and urban planning. The study findings revealed the following: (a) global academic publication landscape for smart city and energy sustainability research;(b) unbalanced publications when critically evaluating geographical continents’ energy use intensity vs. smart cities’ energy sustainability research outcomes;(c) there is a heavy concentration on the technology dimension of energy sustainability and efficiency, and renewables topics in the literature, but much less attention is paid to the energy and urban planning issues. The insights generated inform urban and energy authorities and provide scholars with directions for prospective research.

Making a Building Smart with a Co-Created and Continuously Evolving Enjoyable Service Entity—Insights from a Collaborative Study

Buildings shape cities as those cities grow from and nurture people living and working within the built environment. Thus, the conceptualization of smart building should be brought closer to the smart city initiatives that particularly target ensuring and enhancing the sustainability and quality of urban life. In this paper, we propose that a smart building should be interlinked with a smart city surrounding it;it should provide good experiences to its various occupants and it should be in an ongoing state of evolving as an ecosystem, wherein different stakeholders can join to co-produce, co-provide and co-consume services. Smart buildings require a versatile set of smart services based on digital solutions, solutions in the built environment and human activities. We conducted a multiphase collaborative study on new service opportunities guided by a Design Thinking approach. The approach brought people, technology, and business perspectives together and resulted in key service opportunities that have the potential to make the buildings smart and provide enjoyable experience to the occupants who support their living and working activities in smart cities. This paper provides the resulting practical implications as well as proposes future avenues for research.

Does historical data still count? Exploring the applicability of smart building applications in the post-pandemic period.

The emergence of COVID-19 pandemic is causing tremendous impact on our daily lives, including the way people interact with buildings. Leveraging the advances in machine learning and other supporting digital technologies, recent attempts have been sought to establish exciting smart building applications that facilitates better facility management and higher energy efficiency. However, relying on the historical data collected prior to the pandemic, the resulting smart building applications are not necessarily effective under the current ever-changing situation due to the drifts of data distribution. This paper investigates the bidirectional interaction between human and buildings that leads to dramatic change of building performance data distributions post-pandemic, and evaluates the applicability of typical facility management and energy management applications against these changes. According to the evaluation, this paper recommends three mitigation measures to rescue the applications and embedded machine learning algorithms from the data inconsistency issue in the post-pandemic era. Among these measures, incorporating occupancy and behavioural parameters as independent variables in machine learning algorithms is highlighted. Taking a Bayesian perspective, the value of data is exploited, historical or recent, pre- and post-pandemic, under a people-focused view.