Relevant bibliographies by topics / Privacy for smart buildings

Academic literature on the topic 'Privacy for smart buildings'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Privacy for smart buildings"

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Lee, Sangyoon, Le Xie, and Dae-Hyun Choi. "Privacy-Preserving Energy Management of a Shared Energy Storage System for Smart Buildings: A Federated Deep Reinforcement Learning Approach." Sensors 21, no. 14 (July 19, 2021): 4898. http://dx.doi.org/10.3390/s21144898.

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This paper proposes a privacy-preserving energy management of a shared energy storage system (SESS) for multiple smart buildings using federated reinforcement learning (FRL). To preserve the privacy of energy scheduling of buildings connected to the SESS, we present a distributed deep reinforcement learning (DRL) framework using the FRL method, which consists of a global server (GS) and local building energy management systems (LBEMSs). In the framework, the LBEMS DRL agents share only a randomly selected part of their trained neural network for energy consumption models with the GS without consumer’s energy consumption data. Using the shared models, the GS executes two processes: (i) construction and broadcast of a global model of energy consumption to the LBEMS agents for retraining their local models and (ii) training of the SESS DRL agent’s energy charging and discharging from and to the utility and buildings. Simulation studies are conducted using one SESS and three smart buildings with solar photovoltaic systems. The results demonstrate that the proposed approach can schedule the charging and discharging of the SESS and an optimal energy consumption of heating, ventilation, and air conditioning systems in smart buildings under heterogeneous building environments while preserving the privacy of buildings’ energy consumption.
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Santana, Juan Ramon, Luis Sanchez, Pablo Sotres, Jorge Lanza, Tomas Llorente, and Luis Munoz. "A Privacy-Aware Crowd Management System for Smart Cities and Smart Buildings." IEEE Access 8 (2020): 135394–405. http://dx.doi.org/10.1109/access.2020.3010609.

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Croce, Daniele, Fabrizio Giuliano, Ilenia Tinnirello, and Laura Giarré. "Privacy-Preserving Overgrid: Secure Data Collection for the Smart Grid." Sensors 20, no. 8 (April 16, 2020): 2249. http://dx.doi.org/10.3390/s20082249.

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In this paper, we present a privacy-preserving scheme for Overgrid, a fully distributed peer-to-peer (P2P) architecture designed to automatically control and implement distributed Demand Response (DR) schemes in a community of smart buildings with energy generation and storage capabilities. To monitor the power consumption of the buildings, while respecting the privacy of the users, we extend our previous Overgrid algorithms to provide privacy preserving data aggregation (PP-Overgrid). This new technique combines a distributed data aggregation scheme with the Secure Multi-Party Computation paradigm. First, we use the energy profiles of hundreds of buildings, classifying the amount of “flexible” energy consumption, i.e., the quota which could be potentially exploited for DR programs. Second, we consider renewable energy sources and apply the DR scheme to match the flexible consumption with the available energy. Finally, to show the feasibility of our approach, we validate the PP-Overgrid algorithm in simulation for a large network of smart buildings.
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Li, Depeng, Zeyar Aung, Srinivas Sampalli, John Williams, and Abel Sanchez. "Privacy Preservation Scheme for Multicast Communications in Smart Buildings of the Smart Grid." Smart Grid and Renewable Energy 04, no. 04 (2013): 313–24. http://dx.doi.org/10.4236/sgre.2013.44038.

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Beugin, Yohan, Quinn Burke, Blaine Hoak, Ryan Sheatsley, Eric Pauley, Gang Tan, Syed Rafiul Hussain, and Patrick McDaniel. "Building a Privacy-Preserving Smart Camera System." Proceedings on Privacy Enhancing Technologies 2022, no. 2 (March 3, 2022): 25–46. http://dx.doi.org/10.2478/popets-2022-0034.

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Abstract Millions of consumers depend on smart camera systems to remotely monitor their homes and businesses. However, the architecture and design of popular commercial systems require users to relinquish control of their data to untrusted third parties, such as service providers (e.g., the cloud). Third parties therefore can (and in some instances have) access the video footage without the users’ knowledge or consent—violating the core tenet of user privacy. In this paper, we present CaCTUs, a privacy-preserving smart Camera system Controlled Totally by Users. CaCTUs returns control to the user; the root of trust begins with the user and is maintained through a series of cryptographic protocols, designed to support popular features, such as sharing, deleting, and viewing videos live. We show that the system can support live streaming with a latency of 2 s at a frame rate of 10 fps and a resolution of 480 p. In so doing, we demonstrate that it is feasible to implement a performant smart-camera system that leverages the convenience of a cloud-based model while retaining the ability to control access to (private) data.
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Sater, Raed Abdel, and A. Ben Hamza. "A Federated Learning Approach to Anomaly Detection in Smart Buildings." ACM Transactions on Internet of Things 2, no. 4 (November 30, 2021): 1–23. http://dx.doi.org/10.1145/3467981.

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Internet of Things (IoT) sensors in smart buildings are becoming increasingly ubiquitous, making buildings more livable, energy efficient, and sustainable. These devices sense the environment and generate multivariate temporal data of paramount importance for detecting anomalies and improving the prediction of energy usage in smart buildings. However, detecting these anomalies in centralized systems is often plagued by a huge delay in response time. To overcome this issue, we formulate the anomaly detection problem in a federated learning setting by leveraging the multi-task learning paradigm, which aims at solving multiple tasks simultaneously while taking advantage of the similarities and differences across tasks. We propose a novel privacy-by-design federated learning model using a stacked long short-time memory (LSTM) model, and we demonstrate that it is more than twice as fast during training convergence compared to the centralized LSTM. The effectiveness of our federated learning approach is demonstrated on three real-world datasets generated by the IoT production system at General Electric Current smart building, achieving state-of-the-art performance compared to baseline methods in both classification and regression tasks. Our experimental results demonstrate the effectiveness of the proposed framework in reducing the overall training cost without compromising the prediction performance.
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., Indrawati, Angdini Nurillaily, Husni Amani, and S. K. B. Pillai. "Measuring Smart Building Readiness Index: A Case Study of Bandung City." Jurnal Manajemen Indonesia 20, no. 2 (August 30, 2020): 133. http://dx.doi.org/10.25124/jmi.v20i2.3201.

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Government and private players started focusing on developing cities in to smart cities due to increased level of urbanization in most of the countries around the world, including in Indonesia, by focusing on developing new smart buildings and upgrading old ones. Present paper tried to find out the Smart Building Readiness Index (SBRI) of Bandung City for knowing the level of awareness among the general public based on an exploratory research, the result of which enables the authorities to take strategic initiatives for improving the smart buildings and then to smart city status. Required data was collected by conducting in-depth interviews with 30 respondents and the result of the qualitative data revealed that Bandung’s SBRI comes to only 64.39, which is not a good indicator but within the limits of fairness and needs lot of improvement in future. The result also can be considered as an indicator that annual energy consumption in Bandung city is still at a high level and needs to focus on improving the quality of buildings in and around Bandung city for the purpose of overall reduction in energy consumption and improvement in quality of environment as well as quality of life. Respondents are also not fully aware of the smart building concept. Much needs to be done for making the public aware of the concept of smart building and its usefulness along with strategically developing smart buildings so that in future Bandung city transforms into a smart city with smart buildings. Keywords— Smart City; Smart Building Readiness Index; Bandung.
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Faddel, Samy, Guanyu Tian, and Qun Zhou. "Decentralized Management of Commercial HVAC Systems." Energies 14, no. 11 (May 24, 2021): 3024. http://dx.doi.org/10.3390/en14113024.

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With the growth of commercial building sizes, it is more beneficial to make them “smart” by controlling the schedule of the heating, ventilation, and air conditioning (HVAC) system adaptively. Single-building-based scheduling methods are more focused on individual interests and usually result in overlapped schedules that can cause voltage deviations in their microgrid. This paper proposes a decentralized management framework that is able to minimize the total electricity costs of a commercial microgrid and limit the voltage deviations. The proposed scheme is a two-level optimization where the lower level ensures the thermal comfort inside the buildings while the upper level consider system-wise constraints and costs. The decentralization of the framework is able to maintain the privacy of individual buildings. Multiple data-driven building models are developed and compared. The effect of the building modeling on the overall operation of coordinated buildings is discussed. The proposed framework is validated on a modified IEEE 13-bus system with different connected types of commercial buildings. The results show that coordinated optimization outperforms the commonly used commercial controller and individual optimization of buildings. The results also show that the total costs are greatly affected by the building modeling.
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Aliero, Muhammad Saidu, Muhammad Asif, Imran Ghani, Muhammad Fermi Pasha, and Seung Ryul Jeong. "Systematic Review Analysis on Smart Building: Challenges and Opportunities." Sustainability 14, no. 5 (March 4, 2022): 3009. http://dx.doi.org/10.3390/su14053009.

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Smart building technology incorporates efficient and automated controls and applications that use smart energy products, networked sensors, and data analytics software to monitor environmental data and occupants’ energy consumption habits to improve buildings’ operation and energy performance. Smart technologies and controls are becoming increasingly important not only in research and development (R&D) but also in industrial and commercial domains, leading to a steady growth in their application in the building sector. This study examines the literature on SBEMS published between 2010 and 2020 with a systematic approach. It examines the trend with the annual number of the published studies before exploring the classification of publications in terms of factors such as domain of SBEMS, control approaches, smart technologies, and quality attributes. Recent developments around the smart building energy management systems (SBEMS) have focused on features that provide occupants with an interface to monitor, schedule, and modify building energy consumption profiles and allow a utility to participate in a communication grid through demand response programs and automatic self-report outage functionality. The study also explores future research avenues, especially in terms of improvements in privacy and security, and interoperability. It is also suggested that the smart building technologies’ smartness can be improved with the help of solutions such as real-time data monitoring and machine learning
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Förderer, Kevin, Manuel Lösch, Ralf Növer, Marilen Ronczka, and Hartmut Schmeck. "Smart Meter Gateways: Options for a BSI-Compliant Integration of Energy Management Systems." Applied Sciences 9, no. 8 (April 19, 2019): 1634. http://dx.doi.org/10.3390/app9081634.

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The introduction of Smart Meter Gateways (SMGWs) to buildings and households creates new opportunities and challenges for energy management systems. While SMGWs provide interfaces for accessing recorded information and enable communication to external parties, they also restrict data access to protect the privacy of inhabitants and facility owners. This paper presents an analysis of options for integrating automated (Building) Energy Management Systems (EMSs) into the smart meter architecture based on the technical guidelines for SMGWs by the German Federal Office for Information Security (“Bundesamt für Sicherheit in der Informationstechnik”, BSI). It shows that there are multiple ways for integrating automated EMSs into the German smart metering architecture, although each option comes with its own advantages and restrictions. By providing a detailed discussion of trade-offs, this paper supports EMS designers that will be confronted with differing freedoms and limitations depending on the integration option.
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Dissertations / Theses on the topic "Privacy for smart buildings"

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Shirima, Emil. "Privacy Aware Smart Surveillance." Kent State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=kent1563281303729063.

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Batistic, Kristina. "Privacy in Smart Parking." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-272998.

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The master thesis project will analyze the smart parking solution used in Frederiksberg municipality, focusing on privacy aspects in different data use cases. The current use case will be analyzed with the focus on its privacy aspects. Frederiksberg municipality is using a camera mounted on a car that records parked cars to check whether parking fee has been paid or not. The system recognizes the license plate out of the picture and checks in the system whether the parking for that license plate has been paid or not if it has not been paid it notifies the parking guard to go to the parked car and hand out a parking ticket. Since the license plate is considered personal data, this system has to follow the legal and other obligations for the handling of personal data, i.e., the new European General Data Protection Regulation. Frederiksberg municipality is also considering using data for secondary purposes, such as parking statistics, input for future regulation, analysis to improve the parking system or even making the data public. This thesis will analyze possible secondary use cases and their privacy impacts and recomn measures. The goal is to protect citizens privacy while providing with the best possible service.
Examensarbetet kommer att analysera den smarta parkeringslösningen som används i Frederiksbergs kommun med fokus på sekretessaspekter i olika fall för dataanvändning. Det aktuella användningsfallet kommer att analyseras med fokus på dess integritetsaspekter. Frederiksberg kommun använder en kamera monterad på en bil som registrerar parkerade bilar för att kontrollera om parkeringsavgiften har betalats eller inte. Systemet känner igen registreringsskylten ur bilden och kontrollerar i systemet om parkeringen för den typskylten har betalats eller inte om den inte har betalats, meddelar parkeringsvakten att gå till den parkerade bilen och dela ut en parkeringsbiljett. Eftersom licensskylten betraktas som personuppgifter måste detta system följa de lagliga och andra skyldigheterna för hantering av personuppgifter, dvs. den nya förordningen om europeisk allmän dataskydd. Frederiksberg kommun överväger också att använda data för sekundära ändamål, som parkeringsstatistik, input för framtida reglering, analys för att förbättra parkeringssystemet eller till och med offentliggöra uppgifterna. Denna avhandling kommer att analysera eventuella fall av sekundär användning och deras inverkan på sekretess och rekommendera skyddsåtgärder. Målet skydda medborgarnas integritet samtidigt som de ger bästa möjliga service.
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Falcey, Jonathan M. "Electricity Markets, Smart Grids and Smart Buildings." Thesis, University of Denver, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=1536975.

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A smart grid is an electricity network that accommodates two-way power flows, and utilizes two-way communications and increased measurement, in order to provide more information to customers and aid in the development of a more efficient electricity market. The current electrical network is outdated and has many shortcomings relating to power flows, inefficient electricity markets, generation/supply balance, a lack of information for the consumer and insufficient consumer interaction with electricity markets. Many of these challenges can be addressed with a smart grid, but there remain significant barriers to the implementation of a smart grid.

This paper proposes a novel method for the development of a smart grid utilizing a bottom up approach (starting with smart buildings/campuses) with the goal of providing the framework and infrastructure necessary for a smart grid instead of the more traditional approach (installing many smart meters and hoping a smart grid emerges). This novel approach involves combining deterministic and statistical methods in order to accurately estimate building electricity use down to the device level. It provides model users with a cheaper alternative to energy audits and extensive sensor networks (the current methods of quantifying electrical use at this level) which increases their ability to modify energy consumption and respond to price signals

The results of this method are promising, but they are still preliminary. As a result, there is still room for improvement. On days when there were no missing or inaccurate data, this approach has R2 of about 0.84, sometimes as high as 0.94 when compared to measured results. However, there were many days where missing data brought overall accuracy down significantly. In addition, the development and implementation of the calibration process is still underway and some functional additions must be made in order to maximize accuracy. The calibration process must be completed before a reliable accuracy can be determined.

While this work shows that a combination of a deterministic and statistical methods can accurately forecast building energy usage, the ability to produce accurate results is heavily dependent upon software availability, accurate data and the proper calibration of the model. Creating the software required for a smart building model is time consuming and expensive. Bad or missing data have significant negative impacts on the accuracy of the results and can be caused by a hodgepodge of equipment and communication protocols. Proper calibration of the model is essential to ensure that the device level estimations are sufficiently accurate. Any building model which is to be successful at creating a smart building must be able to overcome these challenges.

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Mao, Congcong. "Privacy Issues in IoT : Privacy concerns in smart home." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-90587.

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In a world of the Internet of Things, smart home has shown a great potency and trend. A smart home is a convenient home setup where appliances and devices can be automatically controlled remotely from any internet-connected place in the world using a mobile or other networked device. Smart home has changed the way the residents interacted with their home and realised more convenience. Although this technology also has positive impact on saving energy and resources, privacy issues in it have shown to one of the biggest obstacles to the adaption of this technology. The purpose of this thesis is to study smart home users’ perceptions of smart homes and their privacy awareness and concerns. The research was conducted through interviews and followed an interpretive research paradigm and a qualitative research approach. In this study, 5 smart home owners were interviewed to investigate their reasons for purchasing IoT devices, their perceptions of smart home privacy risks, and actions to protect their privacy, as well as managing IoT devices and/or its data. The research results show that there are privacy risks existing in smart homes. Consumers’ privacy data is collected secretly, which needs to be controlled, and privacy issues have to be addressed in the near future for the smart home to be fully adopted by the society.
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Tilaveridis, Ioannis, and Kirill Narmack. "PID in Smart Buildings." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-200529.

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Regard, Mikael. "PID in Smart Buildings." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-200567.

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Ahmed, Shadman, and Oguzhan Ugur. "PID in Smart Buildings." Thesis, KTH, Skolan för teknikvetenskap (SCI), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210829.

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This paper investigates a smart heat control system inside a household using a family of dynamic controllers called PID (Proportional Integrative Derivative), conducted with Wireless Sensor Networks (WSN). The laws of thermodynamics and other physical knowledge was used to model the effect that a heat exchanger has on the temperature of a room. Realistic simulations have been run to illustrate how a PID control system outperforms the traditional on-off approach, in terms of energy efficiency. Simulations shows that the PID controlled system is 28% more energy efficient than an on-off. This can make the future use of PIDs in home automation more common. Lastly a future extension to other systems is discussed.
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Grenholm, Sven, and Irini Gionis. "PID in Smart Buildings." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-214702.

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This work details the design and implementationof PID controllers in smart buildings coupled with the useof Wireless Sensor Networks. The main application that isinvestigated is the control of air temperature in a building. Twomathematical models of this system are presented: a simplifiedfirst order system, and a more complex second order system,both based on physical knowledge. Additionally, both modelsare based on a physical implementation to be tested. Three PIDcontrollers have been designed to control this system, two for thefirst order model and one for the second order model. A physicaltest-bed has been implemented with a styrofoam box acting as abuilding. The performance of the controllers and the quality ofthe mathematical description has been investigated by comparingthe simulations and the experimental results. The effect of aconstant feedback delay was simulated using F2 and the systemappeared to be highly resistant to the effects of the delay. Thefirst order system proved to be a better system description,and the second controller F2 had the best performance. Theeffects of packet loss upon the system is also investigated anda well-functioning compensation method is proposed. Finally, afew further areas of applications for PID control in buildingsare discussed, such as ventilation, air humidity, and hydroponicfarming.
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Misagh, Mohammadhadi. "Promoting Privacy in Smart Space." Thesis, KTH, Kommunikationsnät, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-137111.

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The Smart Metering Systems are state of the art technologies and modern services integratedwith legacy metering systems. These systems are one of the most important parts of smart grids.Smart Grids are electrical power infrastructures that make intelligent decisions about the state ofthe electrical power devices. Smart Grids provide a stable electrical power environment. SmartGrids support all functionalities of traditional power systems in addition a Smart Grid bears newfunctionalities of intelligent power systems e.g. self-healing, resisting to attacks, increasingpower quality, motivating consumers to wisely use the electricity, enabling new business toelectrical markets, optimizing assets and operating efficiently and accommodating all generationand storages options. A smart home is usually a modern home that is equipped with some specialstructured wiring or wireless systems to enable inhabitants to remotely control or program any ofhome electronic devices supporting specific types of control functionalities by entering a singlecommand at their remote computer or smart phones. Privacy in smart spaces/environments is notonly confidentiality of data /connections but is the management of the complication of theseenvironments due to decentralised and dynamic nature of these spaces. General model of smarthome and smart metering systems have their specific considerations e.g. assumptions, threats,countermeasures and privacy preserving model. Both security architectures have their specificsecurity policies, considerations, authorization and authentication authorities, and encryption anddecryption strategies. Running two different security architectures in parallel may raise someissues, threats and considerations that are the main purpose of this thesis project. So, theprinciple goal of this research project is to define the secure model of collaboration between twodifferent security architectures in the smart space in which general smart home networkarchitecture is established in parallel to smart metering system architecture. Federatedauthentication systems e.g. SAML and OAuth, OpenID and federated authorization systems likeXACML are most common distributed standard protocols to manage distributed securitysystems. This thesis investigates issues and problems of two parallel security architectures andproposes a secure communication protocol in addition to a proof-of-concept of the final solution.All of most famous available protocols for authentication and authorization will be discussed andfinally will be implemented as a proof of concept. Encryption and decryption as basic securityfunctions is not considered in this project and will be postponed as a future work around thisresearch project.
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Li, Jianing. "Shared smart energy storage system for smart homes and smart buildings." Thesis, University of Birmingham, 2016. http://etheses.bham.ac.uk//id/eprint/6728/.

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In recent years, energy crisis and climate changes have raised a significant attention globally. There’s an increasing awareness of maximising the utilisation of distributed energy resources to ease local network congestion, reduce carbon emissions and even support the grid. This thesis presents a shared energy storage system across multiple apartments to reduce investment and operation costs. Both hardware integration solution and software Cloud connected energy management system are designed and implemented. The solution has been deployed and trialled in residential building block running for two years in a pilot project. The performance of is evaluated through data analytics from the deployed systems. The business model for the above system is proposed and explored. The optimisation is enhanced with various energy services based on fuzzy logic rules to manage controllable loads and incorporate with grid tariffs are designed and evaluated. The feasibility and performance of the proposed energy services is validated through simulation platform with load and generation data profiles extracted from the deployed systems. An aggregated energy management services for apartment buildings is proposed. Business models with incentive scheme are exploited to minimise the operation cost. Its performance is conducted in case studies through various scenarios.
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Books on the topic "Privacy for smart buildings"

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Swathika, O. V. Gnana, K. Karthikeyan, and Sanjeevikumar Padmanaban. Smart Buildings Digitalization. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003201069.

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Swathika, O. V. Gnana, K. Karthikeyan, and Sanjeevikumar Padmanaban. Smart Buildings Digitalization. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003240853.

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Christine, Hertzog, ed. Data privacy for the smart grid. Boca Raton: CRC Press, Taylor & Francis Group, 2015.

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Boroojeni, Kianoosh G., M. Hadi Amini, and S. S. Iyengar. Smart Grids: Security and Privacy Issues. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-45050-6.

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Abdallah, Asmaa, and Xuemin Shen. Security and Privacy in Smart Grid. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93677-2.

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Wright, Tom. Smart cards. [Toronto, Ont: Information and Privacy Commissioner/Ontario, 1993.

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Kayem, Anne V. D. M., Stephen D. Wolthusen, and Christoph Meinel, eds. Smart Micro-Grid Systems Security and Privacy. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91427-5.

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Hansen, Marit, Eleni Kosta, Igor Nai-Fovino, and Simone Fischer-Hübner, eds. Privacy and Identity Management. The Smart Revolution. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92925-5.

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A smart kid's guide to Internet privacy. New York: PowerKids Press, 2010.

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Tomar, Anuradha, Phuong H. Nguyen, and Sukumar Mishra, eds. Control of Smart Buildings. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0375-5.

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Book chapters on the topic "Privacy for smart buildings"

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Wendzel, Steffen, Jernej Tonejc, Jaspreet Kaur, and Alexandra Kobekova. "Cyber Security of Smart Buildings." In Security and Privacy in Cyber-Physical Systems, 327–51. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119226079.ch16.

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Boyer, Jodie P., Kaijun Tan, and Carl A. Gunter. "Privacy Sensitive Location Information Systems in Smart Buildings." In Security in Pervasive Computing, 149–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11734666_12.

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Harper, Scott, Maryam Mehrnezhad, and John C. Mace. "User Privacy Concerns and Preferences in Smart Buildings." In Lecture Notes in Computer Science, 85–106. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79318-0_5.

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McCreary, Faith, Alexandra Zafiroglu, and Heather Patterson. "The Contextual Complexity of Privacy in Smart Homes and Smart Buildings." In HCI in Business, Government, and Organizations: Information Systems, 67–78. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39399-5_7.

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Qureshi, Amna, M. Shahwaiz Afaqui, and Julián Salas. "IoTFC: A Secure and Privacy Preserving Architecture for Smart Buildings." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 102–19. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66922-5_7.

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Al-Sudani, Ahmed Raad, Shang Gao, Sheng Wen, and Muhmmad Al-Khiza’ay. "Secure and Privacy Preserving RFID Based Access Control to Smart Buildings." In Security, Privacy, and Anonymity in Computation, Communication, and Storage, 146–55. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05345-1_12.

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Burton, Craig, Seona Candy, and Behzad Rismanchi. "Sharing Urban Renewable Energy Generation Systems as Private Energy Commons." In Smart and Sustainable Cities and Buildings, 407–17. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37635-2_28.

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Chandrakanth, P., and M. S. Anbarasi. "Privacy Preserving in Data Stream Mining Using Statistical Learning Methods for Building Ensemble Classifier." In Smart Intelligent Computing and Applications, 631–38. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1927-3_66.

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Moroni, Stefano, Anita De Franco, and Beatrice Maria Bellè. "Vacant Buildings. Distinguishing Heterogeneous Cases: Public Items Versus Private Items; Empty Properties Versus Abandoned Properties." In Abandoned Buildings in Contemporary Cities: Smart Conditions for Actions, 9–18. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-35550-0_2.

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Brenes, Edwin, Jorge Chavarría, Diego Murillo, Lucía Sanahuja, Sheng Wang, Adrián Lara, Gustavo López, Luis Quesada, and Jose Antonio Brenes. "User - Smart Building Interactions: An Analysis of Privacy and Productivity Human Factors." In Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022), 815–20. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-21333-5_80.

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Conference papers on the topic "Privacy for smart buildings"

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Wu, Tong, Murtadha Aldeer, Tahiya Chowdhury, Amber Haynes, Fateme Nikseresht, Mahsa Pahlavikhah Varnosfaderani, Jiechao Gao, Arsalan Heydarian, Brad Campbell, and Jorge Ortiz. "The smart building privacy challenge." In BuildSys '21: The 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3486611.3492234.

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Alisic, Rijad, Marco Molinari, Philip E. Pare, and Henrik Sandberg. "Ensuring Privacy of Occupancy Changes in Smart Buildings." In 2020 IEEE Conference on Control Technology and Applications (CCTA). IEEE, 2020. http://dx.doi.org/10.1109/ccta41146.2020.9206317.

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Pappachan, Primal, Martin Degeling, Roberto Yus, Anupam Das, Sruti Bhagavatula, William Melicher, Pardis Emami Naeini, et al. "Towards Privacy-Aware Smart Buildings: Capturing, Communicating, and Enforcing Privacy Policies and Preferences." In 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW). IEEE, 2017. http://dx.doi.org/10.1109/icdcsw.2017.52.

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Wang, Nan, and Sid Chi-Kin Chau. "Incentivizing Privacy-Preserving Crowdsensing for Smart Transportation." In BuildSys '20: The 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3408308.3431131.

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Inibhunu, Catherine, and Carolyn McGregor. "Privacy Preserving Framework for Big Data Management in Smart Buildings." In 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE, 2021. http://dx.doi.org/10.1109/percomworkshops51409.2021.9430994.

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Lesueur, Francois, Sabina Surdu, Romuald Thion, Yann Gripay, and Meriam Ben Ghorbel-Talbi. "Palpable Privacy through Declarative Information Flows Tracking for Smart Buildings." In 2014 Ninth International Conference on Availability, Reliability and Security (ARES). IEEE, 2014. http://dx.doi.org/10.1109/ares.2014.25.

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Cardell-Oliver, Rachel, and Harrison Carter-Turner. "Activity-aware privacy protection for smart water meters." In BuildSys '21: The 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3486611.3486650.

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Inibhunu, Catherine, and AM Carolyn McGregor. "A Privacy Preserving Framework for Smart Cities utilising IoT, Smart Buildings and Big Data." In 2020 IEEE 22nd International Conference on High Performance Computing and Communications; IEEE 18th International Conference on Smart City; IEEE 6th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 2020. http://dx.doi.org/10.1109/hpcc-smartcity-dss50907.2020.00197.

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Pathmabandu, Chehara, John Grundy, Mohan Baruwal Chhetri, and Zubair Baig. "An informed consent model for managing the privacy paradox in smart buildings." In ASE '20: 35th IEEE/ACM International Conference on Automated Software Engineering. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3417113.3422180.

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Lee, Phillip, Eun-Jeong Shin, Valerie Guralnik, Sharad Mehrotra, Nalini Venkatasubramanian, and Kevin T. Smith. "Exploring Privacy Breaches and Mitigation Strategies of Occupancy Sensors in Smart Buildings." In the 1st ACM International Workshop. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3364544.3364827.

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Reports on the topic "Privacy for smart buildings"

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Gupte, Jaideep, Sarath MG Babu, Debjani Ghosh, Eric Kasper, and Priyanka Mehra. Smart Cities and COVID-19: Implications for Data Ecosystems from Lessons Learned in India. Institute of Development Studies (IDS), March 2021. http://dx.doi.org/10.19088/sshap.2021.034.

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This brief distils best data practice recommendations through consideration of key issues involved in the use of technology for surveillance, fact-checking and coordinated control during crisis or emergency response in resource constrained urban contexts. We draw lessons from how data enabled technologies were used in urban COVID-19 response, as well as how standard implementation procedures were affected by the pandemic. Disease control is a long-standing consideration in building smart city architecture, while humanitarian actions are increasingly digitised. However, there are competing city visions being employed in COVID-19 response. This is symptomatic of a broader range of tech-based responses in other humanitarian contexts. These visions range from aspirations for technology driven, centralised and surveillance oriented urban regimes, to ‘frugal innovations’ by firms, consumers and city governments. Data ecosystems are not immune from gendered- and socio-political discrimination, and technology-based interventions can worsen existing inequalities, particularly in emergencies. Technology driven public health (PH) interventions thus raise concerns about 1) what types of technologies are appropriate, 2) whether they produce inclusive outcomes for economically and socially disadvantaged urban residents and 3) the balance between surveillance and control on one hand, and privacy and citizen autonomy on the other.
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Gupte, Jaideep, Sarath MG Babu, Debjani Ghosh, Eric Kasper, Priyanka Mehra, and Asif Raza. Smart Cities and COVID-19: Implications for Data Ecosystems from Lessons Learned in India. Institute of Development Studies, March 2022. http://dx.doi.org/10.19088/sshap.2022.004.

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This brief distils best data practice recommendations through consideration of key issues involved in the use of technology for surveillance, fact-checking and coordinated control during crisis or emergency response in resource constrained urban contexts. We draw lessons from how data enabled technologies were used in urban COVID-19 response, as well as how standard implementation procedures were affected by the pandemic. Disease control is a long-standing consideration in building smart city architecture, while humanitarian actions are increasingly digitised. However, there are competing city visions being employed in COVID-19 response. This is symptomatic of a broader range of tech-based responses in other humanitarian contexts. These visions range from aspirations for technology driven, centralised and surveillance oriented urban regimes, to ‘frugal innovations’ by firms, consumers and city governments. Data ecosystems are not immune from gendered- and socio-political discrimination, and technology-based interventions can worsen existing inequalities, particularly in emergencies. Technology driven public health (PH) interventions thus raise concerns about 1) what types of technologies are appropriate, 2) whether they produce inclusive outcomes for economically and socially disadvantaged urban residents and 3) the balance between surveillance and control on one hand, and privacy and citizen autonomy on the other.
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Gupte, Jaideep, Sarath MG Babu, Debjani Ghosh, Eric Kasper, Priyanka Mehra, and Asif Raza. Smart Cities and COVID-19: Implications for Data Ecosystems from Lessons Learned in India. SSHAP, March 2021. http://dx.doi.org/10.19088/sshap.2021.012.

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This brief distils best data practice recommendations through consideration of key issues involved in the use of technology for surveillance, fact-checking and coordinated control during crisis or emergency response in resource constrained urban contexts. We draw lessons from how data enabled technologies were used in urban COVID-19 response, as well as how standard implementation procedures were affected by the pandemic. Disease control is a long-standing consideration in building smart city architecture, while humanitarian actions are increasingly digitised. However, there are competing city visions being employed in COVID-19 response. This is symptomatic of a broader range of tech-based responses in other humanitarian contexts. These visions range from aspirations for technology driven, centralised and surveillance oriented urban regimes, to ‘frugal innovations’ by firms, consumers and city governments. Data ecosystems are not immune from gendered- and socio-political discrimination, and technology-based interventions can worsen existing inequalities, particularly in emergencies. Technology driven public health (PH) interventions thus raise concerns about 1) what types of technologies are appropriate, 2) whether they produce inclusive outcomes for economically and socially disadvantaged urban residents and 3) the balance between surveillance and control on one hand, and privacy and citizen autonomy on the other.
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Haney, Julie M., Susanne M. Furman, and Yasemin Acar. Research Report: User Perceptions of Smart Home Privacy and Security. National Institute of Standards and Technology, November 2020. http://dx.doi.org/10.6028/nist.ir.8330.

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Ehrlich, Paul, and Rick Diamond. Smart Buildings: Business Case and Action Plan. Office of Scientific and Technical Information (OSTI), April 2009. http://dx.doi.org/10.2172/962466.

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Killough, Stephen, Mohammed Olama, Pooran Joshi, Christopher Winstead, Steve Fulton, Dave English, and Christopher Ray. Low-Cost Multi-Modal Wireless Sensor Platform for Smart Buildings. Office of Scientific and Technical Information (OSTI), April 2019. http://dx.doi.org/10.2172/1494003.

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Feng, Philip. Transforming Ordinary Buildings into Smart Buildings via Low-Cost, Self-Powering Wireless Sensors & Sensor Networks. Office of Scientific and Technical Information (OSTI), June 2017. http://dx.doi.org/10.2172/1372099.

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Lambert, Elise, and Katherine Carter. Be SMART Program: A Better Buildings Neighborhoods Program Initiative in Maryland. Office of Scientific and Technical Information (OSTI), May 2014. http://dx.doi.org/10.2172/1130388.

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Brambley, Michael. Smart Monitoring and Diagnostic System (SMDS) for Packaged Air Conditioners and Heat Pumps for Small/Medium Commercial Buildings: Preparation for Commercialization - CRADA 478. Office of Scientific and Technical Information (OSTI), September 2021. http://dx.doi.org/10.2172/1867263.

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Kintner-Meyer, Michael CW, Ross T. Guttromson, Daniel L. Oedingen, and Steffen Lang. Final Report for the Energy Efficient and Affordable Small Commercial and Residential Buildings Research Program - Project 3.3 - Smart Load Control and Grid Friendly Appliances. Office of Scientific and Technical Information (OSTI), July 2003. http://dx.doi.org/10.2172/15004452.

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