Reduction of Artifacts in Capacitive Electrocardiogram Signals of Driving Subjects

The development of smart cars with e-health services allows monitoring of the health condition of the driver. Driver comfort is preserved by the use of capacitive electrodes, but the recorded signal is characterized by large artifacts. This paper proposes a method for reducing artifacts from the ECG signal recorded by capacitive electrodes (cECG) in moving subjects. Two dominant artifact types are coarse and slow-changing artifacts. Slow-changing artifacts removal by classical filtering is not feasible as the spectral bands of artifacts and cECG overlap, mostly in the band from 0.5 to 15 Hz. We developed a method for artifact removal, based on estimating the fluctuation around linear trend, for both artifact types, including a condition for determining the presence of coarse artifacts. The method was validated on cECG recorded while driving, with the artifacts predominantly due to the movements, as well as on cECG recorded while lying, where the movements were performed according to a predefined protocol. The proposed method eliminates 96% to 100% of the coarse artifacts, while the slow-changing artifacts are completely reduced for the recorded cECG signals larger than 0.3 V. The obtained results are in accordance with the opinion of medical experts. The method is intended for reliable extraction of cardiovascular parameters to monitor driver fatigue status.

The choice of rational complex of active safety systems for smart cars

The problem of ensuring road safety affects all elements of the Driver-Car-Road-Environment system. Smart cars equipped with enough traffic assistants can significantly improve road safety. Active vehicle safety systems, including intelligent driver assistance systems and assistants, perform similar road safety functions. With all the variety of possibilities for equipping cars with systems complexes, the need arises to assess the feasibility and profitability of installing a particular complex of systems. For this, it is proposed to apply the methods of multi-criteria assessment. As a result of calculations, the best options for the sets of systems that most widely cover the road situation have been identified.

Identifying and Mitigating Phishing Attack Threats in IoT Use Cases Using a Threat Modelling Approach

Internet of things (IoT) is a technology that enables our daily life objects to connect on the Internet and to send and receive data for a meaningful purpose. In recent years, IoT has led to many revolutions in almost every sector of our society. Nevertheless, security threats to IoT devices and networks are relentlessly disruptive, because of the proliferation of Internet technologies. Phishing is one of the most prevalent threats to all Internet users, in which attackers aim to fraudulently extract sensitive information of a user or system, using fictitious emails, websites, etc. With the rapid increase in IoT devices, attackers are targeting IoT devices such as security cameras, smart cars, etc., and perpetrating phishing attacks to gain control over such vulnerable devices for malicious purposes. In recent decades, such scams have been spreading, and they have become increasingly advanced over time. By following this trend, in this paper, we propose a threat modelling approach to identify and mitigate the cyber-threats that can cause phishing attacks. We considered two significant IoT use cases, i.e., smart autonomous vehicular system and smart home. The proposed work is carried out by applying the STRIDE threat modelling approach to both use cases, to disclose all the potential threats that may cause a phishing attack. The proposed threat modelling approach can support the IoT researchers, engineers, and IoT cyber-security policymakers in securing and protecting the potential threats in IoT devices and systems in the early design stages, to ensure the secure deployment of IoT devices in critical infrastructures.

IOT Based Camera Motion Control System

The robotics and automation industry which is ruled the sectors from manufacturing to household entertainments. It is widely used because of its simplicity and ability to modify to meet changes of needs. The project is designed to develop a robotic vehicle using android application for remote operation attached with wireless camera for monitoring purpose. Recent advances in smart technology design with integration of smart sensors and embedded components have enhanced human life quickly in so many fields such as home automation, smart phones, smart cars, etc. An Android-based control system is proposed which can maintain residential, industrial security and provides an application which remotely controls all the functions and features of home appliances using Internet of Things (IOT). The details of the users and devices are stored in a database on the server. The central device connects to the internet and the application presents the user with a list of devices to interact with. The server manages the users and devices, and handles the communication between the application and the central device. The system proposed will be economical and can be expanded as it allows connection and control of a number of different devices.

Calibrating Best Route Based on Battery Percentage and Availability of Charging Station

The electric vehicle market is increasing rapidly. Smart cars and AI integrated cars are under development for automatic driving. Embedded software is necessary for an electric vehicle to function properly. Almost all cars have inbuilt software navigation purposes. The user's main concern about electric vehicles is the driving range. Electric cars having an inbuilt navigation system that indicates appropriate charging points suitable for the user. The planning route is essential to reach the destination before the battery dies. The software can provide a solution here by analyzing and optimizing the data which is stored in the cloud. Battery swapping can also be done by booking batteries at charge stations before the time of travel. This solution will promote users to drive electric vehicles for even long travels.