A Novel Approach for Deploying Minimum Sensors in Smart Buildings

Buildings, viewed as cyber-physical systems, become smart by deploying Building Management Systems (BMS). They should be aware about the state and environment of the building. This is achieved by developing a sensing system that senses different interesting factors of the building, called as “facets of sensing.” Depending on the application, different facets need to be sensed at various locations. Existing approaches for sensing these facets consist of deploying sensors at all the places so they can be sensed directly. But installing numerous sensors often aggravate the issues of user inconvenience, cost of installation and maintenance, and generation of e-waste. This article proposes how intelligently using the existing information can help to estimate the facets in cyber-physical systems like buildings, thereby reducing the sensors to be deployed. In this article, an optimization framework has been developed, which optimally deploys sensors in a building such that it satisfies BMS requirements with minimum number of sensors. The proposed solution is applied to real-world scenarios with cyber-physical systems. The results indicate that the proposed optimization framework is able to reduce the number of sensors by 59% and 49% when compared to the baseline and heuristic approach, respectively.

Enabling Continuous Commissioning through Building Management Systems

<p>The use and application of energy efficient technologies within new and existing buildings is a growing global trend. However, if they aren’t being commissioned, controlled and operated in an efficient way, are they really making a valid impact on the energy efficiency of our buildings? Building Management Systems (BMS) are installed within large scale non-residential buildings to control and govern the operation of Heating Ventilation and Air-Conditioning systems (HVAC). BMS monitor and process large amounts of data during their day-to-day operation, while the potential usefulness of BMS to implement energy optimising strategies is typically left un-utilised. There is a growing need to reduce building energy demand. Continuous Commissioning (CCx) may offer the potential to achieve this reduction through the ongoing or periodical assessment of building HVAC operation. As CCx is a cyclic process, and because BMS already monitor and process data in their day-to-day operations, they offer a potential, low overhead means of running CCx processes in buildings. This thesis reports a research project which explores this opportunity to assess and improve building operating efficiency by identifying what data and functional capabilities are required of a BMS to facilitate Continuous Commissioning. A systematic assessment of existing research and standards has highlighted a gap in industry knowledge on the specification of data required to implement CCx assessments to HVAC. There was also no definition of what BMS capabilities were important to the Continuous Commissioning process. These research gaps inspired five secondary research questions around which a mixed-method survey was developed and implemented to bridge the gap between BMS and CCx. The research methodology integrated a standard questionnaire and the Delphi method to explore user perceptions and develop a consensus of BMS requirements. Three survey rounds were distributed to New Zealand based industry experts. Each round informed the following round, with an element of feedback provided through the compilation of the previous round’s responses. This process enabled the industry experts to agree or disagree with the proposed consensus or provide an alternative insight to the questions asked. The results of the surveys were compiled to establish a definition of the top five CCx assessments applied to typical HVAC systems, data point trending requirements and BMS functions important to facilitating Continuous Commissioning. These findings were used to create a guideline for specifying BMS to facilitate Continuous Commissioning and create a soft landing for assessing HVAC during the operation phase of a building’s life. The outcome of this research bridges the gap between the specification of Building Management Systems and the requirements of the Continuous Commissioning process.</p>

Enabling Continuous Commissioning through Building Management Systems

<p>The use and application of energy efficient technologies within new and existing buildings is a growing global trend. However, if they aren’t being commissioned, controlled and operated in an efficient way, are they really making a valid impact on the energy efficiency of our buildings? Building Management Systems (BMS) are installed within large scale non-residential buildings to control and govern the operation of Heating Ventilation and Air-Conditioning systems (HVAC). BMS monitor and process large amounts of data during their day-to-day operation, while the potential usefulness of BMS to implement energy optimising strategies is typically left un-utilised. There is a growing need to reduce building energy demand. Continuous Commissioning (CCx) may offer the potential to achieve this reduction through the ongoing or periodical assessment of building HVAC operation. As CCx is a cyclic process, and because BMS already monitor and process data in their day-to-day operations, they offer a potential, low overhead means of running CCx processes in buildings. This thesis reports a research project which explores this opportunity to assess and improve building operating efficiency by identifying what data and functional capabilities are required of a BMS to facilitate Continuous Commissioning. A systematic assessment of existing research and standards has highlighted a gap in industry knowledge on the specification of data required to implement CCx assessments to HVAC. There was also no definition of what BMS capabilities were important to the Continuous Commissioning process. These research gaps inspired five secondary research questions around which a mixed-method survey was developed and implemented to bridge the gap between BMS and CCx. The research methodology integrated a standard questionnaire and the Delphi method to explore user perceptions and develop a consensus of BMS requirements. Three survey rounds were distributed to New Zealand based industry experts. Each round informed the following round, with an element of feedback provided through the compilation of the previous round’s responses. This process enabled the industry experts to agree or disagree with the proposed consensus or provide an alternative insight to the questions asked. The results of the surveys were compiled to establish a definition of the top five CCx assessments applied to typical HVAC systems, data point trending requirements and BMS functions important to facilitating Continuous Commissioning. These findings were used to create a guideline for specifying BMS to facilitate Continuous Commissioning and create a soft landing for assessing HVAC during the operation phase of a building’s life. The outcome of this research bridges the gap between the specification of Building Management Systems and the requirements of the Continuous Commissioning process.</p>

LPWAN Networks for Energy Meters Reading and Monitoring Power Supply Network in Intelligent Buildings

In this paper the idea of functioning of Building Management Systems and Object Management Systems in intelligent buildings is presented. New functionalities of intelligent buildings resulting from the introduction of microgeneration are described. Low-Power Wide-Area Networks (LPWAN) are characterized and compared. The selected Long-Range (LoRaWAN) technology is tested for its use for communication with energy meters and monitoring the power supply network in intelligent buildings. In the paper a new system for reading and monitoring the network is proposed, consisting of hardware, communication, and application layers. A key element of the system is a specially developed converter, which has been designed and tested in a real urban environment. Using our solution in practice could allow to change the architecture of a measurement data acquisition system to much more flexible and efficient.

Design of Multi-Information Fusion Based Intelligent Electrical Fire Detection System for Green Buildings

Building management systems are costly for small- to medium-sized buildings. A massive volume of data is collected on different building contexts by the Internet of Things (IoT), which is then further monitored. This intelligence is integrated into building management systems (BMSs) for energy consumption management in a cost-effective manner. Electric fire safety is paramount in buildings, especially in hospitals. Facility managers focus on fire protection strategies and identify where system upgrades are needed to maintain existing technologies. Furthermore, BMSs in hospitals should minimize patient disruption and be immune to nuisance alarms. This paper proposes an intelligent detection technology for electric fires based on multi-information fusion for green buildings. The system model was established by using fuzzy logic reasoning. The extracted multi-information fusion was used to detect the arc fault, which often causes electrical fires in the low-voltage distribution system of green buildings. The reliability of the established multi-information fusion model was verified by simulation. Using fuzzy logic reasoning and the membership function in fuzzy set theory to solve the uncertain relationship between faults and symptoms is a widely applied method. In order to realize the early prediction and precise diagnosis of faults, a fuzzy reasoning system was applied to analyze the arcs causing electrical fires in the lines. In order to accurately identify the fault arcs that easily cause electrical fires in low-voltage distribution systems for building management, this paper introduces in detail a fault identification method based on multi-information fusion, which can consolidate the complementary advantages of different types of judgment. The results demonstrate that the multi-information fusion method reduces the deficiency of a single criterion in fault arc detection and prevents electrical fires in green buildings more comprehensively and accurately. For the real-time dataset, the data results are presented, showing disagreements among the testing methods.

Review of lighting and daylighting control systems

There is a large number of control systems proposed either by lighting manufacturers or motor manufacturers for shading systems. In addition there are many other solutions proposed by specific manufacturers of Building Management Systems (BMS) or manufacturers of components to be installed in luminaires and switches, as well as in the electric lighting architecture (transformers, gateways to the internet, sensors, etc.). For many consumers -i.e.-the installer, the facility manager, or the final user (building occupant) – this forms a complex and dynamic market environment with high frequent changes, every year or even every month or day. In this report we aim to provide some basic strategic information, showing the status of the supply at the time this report was written (2019-2021). Although the market develops very fast, there are principles of controls which are rather independent of the progress of technology.

BuildCOM: automated auditing and continuous commissioning of next generation building management systems

A building management system (BMS) is generally defined as the ‘Brain’ of the building. Building management systems aid in improving occupant comfort and productivity and, enhance the operational efficiency of building energy generation and supply systems. This paper presents the BuildCOM project which is driven by the industry and customer needs. It responds to the increasing demands for energy efficiency, comfort, and safety in the buildings sector. The project brings together academic researchers, industrial companies and public partners, to develop and demonstrate an innovative first-of-its-kind software for BMS automated auditing and continuous building commissioning. The software has three major capabilities, initial BMS auditing, BMS retro-commissioning and continuous building commissioning. Thus, the proposed software will aid the design, development and operation of next generation building management systems. The project builds up partly on the online building energy performance monitoring and evaluation (ObepME) tool developed in COORDICY which will be combined with a holistic process for building management systems auditing and commissioning within the developed software solution. The set of tools developed under BuildCOM will be implemented and demonstrated considering multiple case studies. Implementing the proposed solution, the customers and building owners will have up to 35% higher energy efficiency in newly built and exiting buildings, around 25% lower operation costs and less emissions from day one and throughout the building operation phase.

Early warning signals of failures in building management systems

In the context of sensor data generated by Building Management Systems (BMS), early warning signals are still an unexplored topic. The early detection of anomalies can help preventing malfunctions of key parts of a heating, cooling and air conditioning (HVAC) system that may lead to a range of BMS problems, from important energy waste to fatal errors in the worst case. We analyse early warning signals in BMS sensor data for early failure detection. In this paper, the studied failure is a malfunction of one specific Air Handling Unit (AHU) control system that causes temperature spikes of up to 30 degrees Celsius due to overreaction of the heating and cooling valves in response to an anomalous temperature change caused by the pre-heat coil in winter period in a specific area of a manufacturing facility. For such purpose, variance, lag-1 autocorrelation function (ACF1), power spectrum (PS) and variational autoencoder (VAE) techniques are applied to both univariate and multivariate scenarios. The univariate scenario considers the application of these techniques to the control variable only (the one that displays the failure), whereas the multivariate analysis considers the variables affecting the control variable for the same purpose. Results show that anomalies can be detected up to 32 hours prior to failure, which gives sufficient time to BMS engineers to prevent a failure and therefore, an proactive approach to BMS failures is adopted instead of a reactive one.

Cloud-Based IoT Architecture for Green Buildings

Green building (GB) is a game changer as the world is moving towards conserving its resources. Green building management systems available nowadays are too expensive and cannot cater to small or medium-sized buildings. Internet of things-based systems use simple, low-cost sensors, signal processing, and high-level learning methods. Studies on building occupancy and human activities help improve design and push the energy conservation levels. With huge amounts of data and improved learning systems, the impetus is to capture the information and use it well to improve design and justify the green building concept. Cloud-based architecture helps to monitor, capture, and process the data, which acts as input to intelligent learning systems, which in turn help to improve the design and performance of current green building management systems. This chapter discusses role of cloud-based internet of things architecture in improving design and performance of current building management systems.