Detecting the Presence of Electronic Devices in Smart Homes Using Harmonic Radar Technology

Data about users is collected constantly by phones, cameras, Internet websites, and others. The advent of so-called ‘Smart Things’ now enable ever-more sensitive data to be collected inside that most private of spaces: the home. The first step in helping users regain control of their information (inside their home) is to alert them to the presence of potentially unwanted electronics. In this paper, we present a system that could help homeowners (or home dwellers) find electronic devices in their living space. Specifically, we demonstrate the use of harmonic radars (sometimes called nonlinear junction detectors), which have also been used in applications ranging from explosives detection to insect tracking. We adapt this radar technology to detect consumer electronics in a home setting and show that we can indeed accurately detect the presence of even ‘simple’ electronic devices like a smart lightbulb. We evaluate the performance of our radar in both wired and over-the-air transmission scenarios.

Carpooling in Smart City using SIoT: Vision, Challenges and Future Scope

Carpooling or Ridesharing is the need of the hour owing to increase in transportation cost, increased traffic congestion due to huge number of vehicles on road etc. Several attempts at proposing efficient ridesharing methods are being made by the researchers and Government authorities of several nations. Each method has its own advantage as well as disadvantage. How to group people who would car-pool is a problem of concern. Their source and destination would play a pivotal role. Knowing their preferred route in advance can be helpful. Now, if we consider the Carpooling problem as a part of a Smart City where any physical object is connected to the network through the Internet of Things (IoT) the problem can be dealt with a different perspective. A lot of work is already there where connected vehicles can communicate with each other through Wireless Sensor Network(WSN) or IOT(Internet of Things). Social Internet of Things (SIOT) deals with the concept that in addition to being smart, things are also social. It is a comparatively novel concept; some interesting works are being done regarding this field. Our article’s primary focus is to provide a review of the recent work regarding ridesharing and SIOT which will help us analyse these concepts and pave a path for future developments in this field.

IoT Security Mechanisms in the Example of BLE

In recent years, a lot of IoT devices, wireless sensors, and smart things contain information that must be transmitted to the server for further processing. Due to the distance between devices, battery power, and the possibility of sudden device failure, the network that connects the devices must be scalable, energy efficient, and flexible. Particular attention must be paid to the protection of the transmitted data. The Bluetooth mesh was chosen as such a network. This network is built on top of Bluetooth Low-Energy devices, which are widespread in the market and whose radio modules are available from several manufacturers. This paper presents an overview of security mechanisms for the Bluetooth mesh network. This network provides encryption at two layers: network and upper transport layers, which increases the level of data security. The network uses sequence numbers for each message to protect against replay attacks. The introduction of devices into the network is provided with an encryption key, and the out-of-band (OOB) mechanism is also supported. At the moment, a comparison has been made between attacks and defense mechanisms that overlap these attacks. The article also suggested ways to improve network resiliency.

Cloud-Based Fault Prediction Using IoT in Office Automation for Improvisation of Health of Employees

The novel paradigm of Internet of Things (IoT) is gaining recognition in the numerous scenarios promoting the pervasive presence of smart things around us through its application in various areas of society, which includes transportation, healthcare, industries, and agriculture. One more such application is in the smart office to monitor the health of devices via machine learning (ML) that makes the equipment more efficient by allowing real-time monitoring of their health. It guarantees indoor comfort as per the user’s satisfaction as it emphasizes on fault prediction in real-life devices. Early identification of various types of faults in IoT devices is the key requirement in smart offices. IoT devices are becoming ubiquitous and provide an assistant to supervise an office that is regulated by ML and data received from sensors is stored in cloud. A recommender system facilitates the selection of an appropriate solution for faults in IoT-enabled devices to mitigate faults. The architecture proposed in this paper is used to monitor each and every office appliance connected via IoT technology using ML technique, and recommender system is used to recommend solutions for fault patterns without much human intervention. The ultrasonic motion sensor is used to fetch the information of employee availability in cubicles and data is sent to the cloud through the WiFi module. ATmega8 is used to control electrical appliances in the office environment. The significance of this work is to forecast the faults in IoT appliances which will have an impact on life and reliability of IoT appliances. The main objective is to design a prototype of a smart office using IoT that can control and automate workplace devices and forecast whether the device needs repairing or replacing, thus reducing the overall burden on the employee and helping out in increasing physical as well as mental health of the person.

Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing

Internet of Things (IoT) is a developing technology for supporting heterogeneous physical objects into smart things and improving the individuals living using wireless communication systems. Recently, many smart healthcare systems are based on the Internet of Medical Things (IoMT) to collect and analyze the data for infectious diseases, i.e., body fever, flu, COVID-19, shortness of breath, etc. with the least operation cost. However, the most important research challenges in such applications are storing the medical data on a secured cloud and make the disease diagnosis system more energy efficient. Additionally, the rapid explosion of IoMT technology has involved many cyber-criminals and continuous attempts to compromise medical devices with information loss and generating bogus certificates. Thus, the increase in modern technologies for healthcare applications based on IoMT, securing health data, and offering trusted communication against intruders is gaining much research attention. Therefore, this study aims to propose an energy-efficient IoT e-health model using artificial intelligence with homomorphic secret sharing, which aims to increase the maintainability of disease diagnosis systems and support trustworthy communication with the integration of the medical cloud. The proposed model is analyzed and proved its significance against relevant systems.

Prospects of IoT technology

Introduction. Internet of Things (IoT) is one of the promising innovative technologies. Every year more and more people are involved in the use of smart things. At the same time, a relatively small number of papers are devoted to the study of the social value of technology and the experience of human interaction with this technology. It is important to study the features and prospects of the technology, to analyze the attitude and willingness of people to use it. Materials and Methods. We have conducted an Internet survey, in which special attention is paid to the place of IoT in the life of modern people, their attitude to the concept of devices. The obtained data is processed and systematized. Results. The analysis of the survey results allowed us to draw conclusions regarding the attitude and willingness of young people to apply this technology. In the course of the study, the IoT concept was defined, the conditions required for the existence and functioning of the technology were described, the advantages of IoT technology were generalized, information technologies interacting with this technology were specified, the tasks that require solutions for the successful and effective implementation of IoT into Russian reality were listed. Discussion and Conclusions. The Internet of Things is a technology that, with a consistent and systematic solution to a number of problems, can become a significant factor in the development of both individual spheres of life and activity, and the country as a whole. At the same time, it is important to study and consider the social impact of technology dissemination. This will increase trust in the IoT and eliminate negative impacts. The survey shows that young people tend to use smart things more widely. It is necessary to expand the range of smart things, to more confidently introduce the basics of practical application of IoT technology into educational programs, to discuss issues, ways to solve the tasks and pilot projects related to this technology widely in the media. This will enable to train not only people who are practically interested in IoT, but also qualified personnel who are able to solve problems in a new way.

A Fuzzy Logic-Based Method for Incorporating Ethics in the Internet of Things

IoT is expected to have far-reaching consequences on society due to a wide spectrum of applications like smart healthcare, smart transportation, smart agriculture, smart home, etc. However, ethical considerations of AI-enabled smart devices have not been duly considered from a design perspective. In this paper, the authors propose a novel fuzzy logic-based method to incorporate ethics within smart things of IoT. Ethical considerations relevant to a machine context are represented in terms of fuzzy ethics variables (FEVs) and ethics rules. For each ethics rule, a value called scaled ethics value (SEV) is used to indicate its ethical desirability. In order to model flexibility in ethical response, the authors employ the concept of ethics modes that selectively allow scenarios depending on the value of SEV. The method offers a viable mechanism for smart devices to imbue ethical sensitivity that can pave the way for a technology society amenable to human ethics. However, the method does not account for varying ethics, as such incorporating learning mechanisms represent a promising research direction.