In the contemporary era, smart buildings, characterized by their integration of advanced technologies to enhance energy efficiency and user experience, are becoming increasingly prevalent. While these advancements offer notable benefits in terms of operational efficiency and sustainability, they concurrently introduce a myriad of privacy concerns. This review article delves into the multifaceted realm of privacy issues associated with energy-efficient smart buildings. We commence by elucidating the potential risks emanating from data collection, storage, and analysis, highlighting the vulnerability of the personal and behavioral information of inhabitants. The article then transitions into discussing the rights of occupants, emphasizing the necessity for informed consent and the ability to opt-out of invasive data collection practices. Lastly, we provide an overview of existing regulations governing the intersection of smart buildings and privacy. We evaluate their effectiveness and present gaps that necessitate further legislative action. By offering a holistic perspective on the topic, this review underscores the pressing need to strike a balance between harnessing the benefits of technology in smart buildings and safeguarding the privacy of their occupants.

There are many methods or algorithms applicable for detecting electricity theft. However, comparative studies on supervised learning methods for electricity theft detection are still insufficient. In this paper, comparisons based on predictive accuracy, recall, precision, AUC, and F1-score of several supervised learning methods such as decision tree (DT), artificial neural network (ANN), deep artificial neural network (DANN), and AdaBoost are presented and their performances are analyzed. A public dataset from the State Grid Corporation of China (SGCC) was used for this study. The dataset consisted of power consumption in kWh unit. Based on the analysis results, the DANN outperforms compared to other supervised learning classifiers such as ANN, AdaBoost, and DT in recall, F1-Score, and AUC. A future research direction is the experiments can be performed on other supervised learning algorithms with different types of datasets and suitable preprocessing methods can be applied to produce better performance.

Buildings are one of the highest energy consumption contributors in the construction sector in Malaysia. Some parameters are acknowledged as the factors that influence the efficiency of building energy, including climate conditions, location and type of buildings. Optimizing the energy efficiency of buildings is a more economical strategy to reduce energy consumption, especially for tropical climates, and Malaysia naturally has plenty of sunlight and consistency throughout the year. Therefore, this paper discusses Malaysia different building designs and policies to improve energy consumption and efficiency of office buildings in Malaysia. In addition, the limitations encountered and the initiatives implemented by the Malaysian government in improving energy usage in the office building are also included. This review is expected to provide a framework and explanation that can be used as a guide to identify which approach is most appropriate to help optimize energy efficiency for buildings in developing and tropical countries such as Malaysia.

Wireless sensor networks have received a great attention since they emerged as new ways of communicating and distributing information in wireless network. However the security aspect of wireless sensor network remains an issue, namely authentication, key management and secure localization. Since the communication of wireless sensor is on broadcast basis, researchers are focusing on how to design an efficient authentication scheme since the data might lost during the transmission and this is crucial for entity authentication prior the actual communication. Entity or user authenticity is important to avoid forgery and replay attack. This paper will focus on authentication by investigating three authentication schemes based on user authentication for Wireless Sensor Network. We identify their weakness and we finally introduce a new scheme which is based on identity-bits commitment for authentication that overcomes problems identified in studied schemes. A basic security analysis is followed to support the strength of the scheme in a real deployment.