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- Abuimara, Tareq, et al.
(författare)
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Detailed Case Studies
- 2023
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Ingår i: Occupant-Centric Simulation-Aided Building Design. - 9781000865752 ; , s. 257-367
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Wireless body area networks (WBANs) are one of the key technologies that support the development of pervasive health monitoring (remote patient monitoring systems), which has attracted more attention in recent years. These WBAN applications requires stringent security requirements as they are concerned with human lives. In the recent scenario of the corona pandemic, where most of the healthcare providers are giving online services for treatment, DDoS attacks become the major threats over the internet. This chapter particularly focusses on detection of DDoS attack using machine learning algorithms over the healthcare environment. In the process of attack detection, the dataset is preprocessed. After preprocessing the dataset, the cleaned dataset is given to the popular classification algorithms in the area of machine learning namely, AdaBoost, J48, k-NN, JRip, Random Committee and Random Forest classifiers. Those algorithms are evaluated independently and the results are recorded. Results concluded that J48 outperform with accuracy of 99.98% with CICIDS dataset and random forest outperform with accuracy of 99.917, but it takes the longest model building time. Depending on the evaluation performance the appropriate classifier is selected for further DDoS detection at real-time.
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- Walther, Karl, et al.
(författare)
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The role of HVAC controls in building Digital Twins : lessons learned from demonstration buildings with an application to air handling units
- 2023
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Ingår i: BS 2023 - Proceedings of Building Simulation 2023: 18th Conference of IBPSA. - : International Building Performance Simulation Association. ; , s. 2005-2012
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Konferensbidrag (refereegranskat)abstract
- This study investigates how information about the controls of heating, ventilation and air-conditioning (HVAC) systems can be gathered from building automation systems for the creation of Digital Twins in Building Performance Simulation (BPS). The concept of Digital Twins in BPS environments is commonly used for Fault Detection and Diagnosis or performance gap analysis during operation. In the creation, often emphasis is put on building physics or user behavior. In modern buildings, automation systems play an important role to guarantee user comfort requirements as well as an energy efficient operation. To replicate the behavior of real HVAC systems in Building Performance Simulations, the underlying control logic has to be known. To gather this information in operation we have investigated three sources: firstly, documentation from the design phase including already existing simulation models, secondly, the control code on automation systems and thirdly, reverse engineering from measured data. The study focuses on air handling units and is based on experiences in state-of-the-art building demonstrators from research projects in Sweden and Germany.
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