The Internet of Things (IoT) is entering the daily operation of many industries; applications include but are not limited to smart cities, smart grids, smart homes, physical security, e-health, asset management, and logistics. For example, the concept of smart cities is emerging in multiple continents, where enhanced street lighting controls, infrastructure monitoring, public safety and surveillance, physical security, gunshot detection, meter reading, and transportation analysis and optimization systems are being deployed on a city-wide scale. A related and cost-effective user-level IoT application is the support of IoT-enabled smart buildings. Commercial space has substantial requirements in terms of comfort, usability, security, and energy management. IoT-based systems can support these requirements in an organic manner. In particular, power over Ethernet, as part of an IoT-based solution, offers disruptive opportunities in revolutionizing the in-building connectivity of a large swath of devices. However, a number of deployment-limiting issues currently impact the scope of IoT utilization, including lack of comprehensive end-to-end standards, fragmented cybersecurity solutions, and a relative dearth of fully-developed vertical applications. This paper reviews some of the technical opportunities offered and the technical challenges faced by the IoT in the smart building arena.

IoT Considerations, Requirements, and Architectures for Smart Buildings—Energy Optimization and Next-Generation Building Management Systems

A review of smart home applications based on Internet of Things

A flexible, ultra-highly sensitive and stable capacitive pressure sensor with convex microarrays for motion and health monitoring

Anomaly detection is a problem with applications for a wide variety of domains; it involves the identification of novel or unexpected observations or sequences within the data being captured. The majority of current anomaly detection methods are highly specific to the individual use case, requiring expert knowledge of the method as well as the situation to which it is being applied. The Internet of Things (IoT) as a rapidly expanding field offers many opportunities for this type of data analysis to be implemented, however, due to the nature of the IoT, this may be difficult. This review provides a background on the challenges which may be encountered when applying anomaly detection techniques to IoT data, with examples of applications for the IoT anomaly detection taken from the literature. We discuss a range of approaches that have been developed across a variety of domains, not limited to IoT due to the relative novelty of this application. Finally, we summarize the current challenges being faced in the anomaly detection domain with a view to identifying potential research opportunities for the future.

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Anomaly Detection for IoT Time-Series Data: A Survey

Adopting Internet of Things for the development of smart buildings: A review of enabling technologies and applications

Our research approach is to design and develop reliable, efficient, flexible, economical, real-time and realistic wellness sensor networks for smart home systems. The heterogeneous sensor and actuator nodes based on wireless networking technologies are deployed into the home environment. These nodes generate real-time data related to the object usage and movement inside the home, to forecast the wellness of an individual. Here, wellness stands for how efficiently someone stays fit in the home environment and performs his or her daily routine in order to live a long and healthy life. We initiate the research with the development of the smart home approach and implement it in different home conditions (different houses) to monitor the activity of an inhabitant for wellness detection. Additionally, our research extends the smart home system to smart buildings and models the design issues related to the smart building environment; these design issues are linked with system performance and reliability. This research paper also discusses and illustrates the possible mitigation to handle the ISM band interference and attenuation losses without compromising optimum system performance.

https://www.mdpi.com/1424-8220/15/5/10350/pdf

WSN- and IOT-Based Smart Homes and Their Extension to Smart Buildings.

Wireless sensor networks (WSNs) provide noteworthy benefits over traditional approaches for several applications, including smart homes, healthcare, environmental monitoring, and homeland security. WSNs are integrated with the Internet Protocol (IP) to develop the Internet of Things (IoT) for connecting everyday life objects to the internet. Hence, major challenges of WSNs include: (i) how to efficiently utilize small size and low-power nodes to implement security during data transmission among several sensor nodes; (ii) how to resolve security issues associated with the harsh and complex environmental conditions during data transmission over a long coverage range. In this study, a secure IoT-based smart home automation system was developed. To facilitate energy-efficient data encryption, a method namely Triangle Based Security Algorithm (TBSA) based on efficient key generation mechanism was proposed. The proposed TBSA in integration of the low power Wi-Fi were included in WSNs with the Internet to develop a novel IoT-based smart home which could provide secure data transmission among several associated sensor nodes in the network over a long converge range. The developed IoT based system has outstanding performance by fulfilling all the necessary security requirements. The experimental results showed that the proposed TBSA algorithm consumed less energy in comparison with some existing methods.

A Novel Secure IoT-Based Smart Home Automation System Using a Wireless Sensor Network.

Computer vision is becoming an increasingly trendy word in the area of image processing. With the emergence of computer vision applications, there is a significant demand to recognize objects automatically. Deep CNN (convolution neural network) has benefited the computer vision community by producing excellent results in video processing, object recognition, picture classification and segmentation, natural language processing, speech recognition, and many other fields. Furthermore, the introduction of large amounts of data and readily available hardware has opened new avenues for CNN study. Several inspirational concepts for the progress of CNN have been investigated, including alternative activation functions, regularization, parameter optimization, and architectural advances. Furthermore, achieving innovations in architecture results in a tremendous enhancement in the capacity of the deep CNN. Significant emphasis has been given to leveraging channel and spatial information, with a depth of architecture and information processing via multi-path. This survey paper focuses mainly on the primary taxonomy and newly released deep CNN architectures, and it divides numerous recent developments in CNN architectures into eight groups. Spatial exploitation, multi-path, depth, breadth, dimension, channel boosting, feature-map exploitation, and attention-based CNN are the eight categories. The main contribution of this manuscript is in comparing various architectural evolutions in CNN by its architectural change, strengths, and weaknesses. Besides, it also includes an explanation of the CNN’s components, the strengths and weaknesses of various CNN variants, research gap or open challenges, CNN applications, and the future research direction.

CNN Variants for Computer Vision: History, Architecture, Application, Challenges and Future Scope

Activity recognition is a popular research area with a number of applications, particularly in the smart home environment. The unique features of smart home sensors have challenged traditional data analysis methods. However, the recognition of anomalous activities is still immature in the smart home when compared with other domains such as computer security, manufacturing defect detection, medical image processing, etc. This chapter reviews smart home’s dense sensing approaches, an extensive review from sensors, data, analysis, algorithms, prompting reminder system, to the recent development of anomaly activity detection.

Activity and Anomaly Detection in Smart Home: A Survey

In recent times, wireless sensor networks (WSNs) have become the backbone of many systems. Smart homes based on WSN protocols are used to provide an assisted living environment to humans. The currently reported smart home systems based on generalized WSN protocols suffer from complexity, large data handling, and data transmission delay. This paper has reported a new protocol especially developed to address smart homes for assisted living. The whole purpose of a smart home is to provide a safe environment for the well-being of its inhabitants. Ergo, the protocol is named as wellness sensor networks. The developed protocol has been used in an old home built in 1938, which was converted into a smart home with the use of sensing technologies.

Hemant Ghayvat

Papers

WSN- and IOT-Based Smart Homes and Their Extension to Smart Buildings.

A Novel Secure IoT-Based Smart Home Automation System Using a Wireless Sensor Network.

CNN Variants for Computer Vision: History, Architecture, Application, Challenges and Future Scope

Activity and Anomaly Detection in Smart Home: A Survey

Wellness Sensor Networks: A Proposal and Implementation for Smart Home for Assisted Living