Research & Review: Electronics and Communication Engineering

Car Door Exit Warning System Using Raspberry Pi and Arduino

2024-01-10T07:08:18+00:00

The Smart Car Door Exit Warning System, featuring cameras for added safety, is a state-of-the-art solution designed to make getting out of a vehicle safer and more secure. By utilizing cameras positioned around the car, this system can detect potential hazards and provide warnings to the occupants and pedestrians, significantly reducing the risk of accidents caused by opening car doors. In this innovative system, strategically placed cameras continuously capture the surroundings of the vehicle, such as nearby traffic, pedestrians, and obstacles. Using advanced image analysis and artificial intelligence, the system can recognize and track objects and people close to the vehicle. When the system identifies a possible danger while a door is being opened, it activates visual and auditory alerts inside the car, alerting both the driver and passengers to the potential risk. Furthermore, it can send these alerts to pedestrians and other road users, promoting greater safety awareness through external notifications. The Smart Car Door Exit Warning System with cameras surpasses conventional proximity sensors by providing more accurate and wider-ranging object recognition. It excels in situations where precise identification and situational awareness are crucial, making it particularly valuable in urban settings with complex traffic conditions and limited parking space. This system represents a significant advancement in reducing accidents related to car door openings, enhancing safety for both vehicle occupants and pedestrians. By employing advanced camera technology and artificial intelligence, it offers a more comprehensive and reliable approach to preventing door-related incidents, thus contributing to safer transportation in an increasingly crowded and urbanized world.

Blockchain Empowering Internet of Things: A Comprehensive Analysis of Applications and Security Challenges

2024-02-09T10:21:04+00:00

An accessible, dependable, and secure infrastructure is necessary to manage the ever-increasing amount of processed data, which is being driven by the proliferation of Internet of Things (IoT) devices in society. There is a risk of single-point failures in the current IoT model because it depends on a central cloud server. One solution to this problem is the increasing popularity of combining Blockchain Technology (BCT) with the IoT. This takes advantage of the decentralized structure of Blockchain (BC) networks. IoT security has been greatly enhanced by this merger. A comprehensive analysis of Blockchain-based Internet of Things (BC-IoT) applications and the security risks they pose is provided in this study. It examines the IoT and BCT side by side, using well-structured and efficient scholarly literature to classify blockchain-based IoT applications in many different industries, such as manufacturing, healthcare, transportation, supply chain management, and ad hoc Vehicle Networks (VANET). In addition, the article discusses the shortcomings of BCT as it pertains to the IoT and the security concerns surrounding applications built on the blockchain. Academics and researchers can use the given insights to further develop BC applications based on the IoT.

Modern Advances in Optical Communications: A Review

2024-01-17T23:04:44+00:00

Since optical fibers are dielectric and can transport a substantial amount of information, they are frequently utilized in the systems that are responsible for the transmission of data. When it comes to applications that are central, metropolitan, or large-scale, network topologies that utilize several wavelengths per optical fiber are utilized to link thousands of users with a variety of transmission speeds and capacities. This is done to facilitate the implementation of these applications. An important characteristic of optical communication networks is the ability to transmit many wavelengths simultaneously through fibers that have a wavelength range that extends from 1300 to 1600 nanometers. Wavelength Division Multiplexing, sometimes known as WDM, is a technique that allows for the mixing of several wavelengths on analogous cables. The Wavelength Division Multiplexing (WDM) principle, when paired with optical amplifiers, results in the production of communication lines that allow for seamless communication between users located in different countries.

The system's dynamism and endurance have been increased, and its possibilities have been expanded, as a result of recent breakthroughs in optical communication. Several cutting-edge technologies have been created to improve the bandwidth of specific wavelength channels as well as the number of wavelengths that are given every year.

The purpose is to provide an overview of recent studies in the field of optical communications. More specifically, we cover topics such as modulation, switching, additive multiplexing, coding schemes, detection schemes, orthogonal frequency division multiplexing, system analysis, cross-layer design, control and management, free space optics, and optics in data centre networks. The primary objectives of this paper are to encourage further research on optical communications, to bring knowledge and awareness of achievements in the field up to date, and to disseminate cutting-edge technology in operational networks.

Battery Health Monitoring and Optimisation System

2024-03-13T05:21:18+00:00

The main goal of this project is to identify possible unusual faults in a lithium-ion battery. Our research aims to use an ESP 32 microcontroller and sensors such as a smoke detector, and temperature sensor to monitor environmental parameters such as the temperature of the lithium-ion battery of an electric car. And also protects it from unwanted situations during loading and unloading by solenoid valve, dangerous fire can be stopped. Also checks for overvoltage, overflow, overheating, and overload and protects the battery. Transport is the basis for the development of every nation around the world. Currently, our dependence on internal combustion engines that use traditional sources as fuel significantly increases environmental pollution. The answer is a transition to electric vehicles, but the current proliferation of internal combustion engine electric cars presents a major challenge to the transition from traditional engines to electric cars. To solve this, our project involves designing a battery protection scheme for electric cars against adverse conditions such as overheating and overcurrent. Maintaining an optimal operating temperature of 20-45℃ is crucial for the lithium-ion batteries that power electric cars around the world. In particular, electric vehicles using lithium-ion batteries offer significant advantages over fuel-dependent vehicles, as they are free from vibration, noise and pollution. This is a Battery Management System (BMS) designed to improve the performance and longevity of rechargeable batteries. The BMS includes advanced monitoring, balancing and control mechanisms to optimize charging and discharging processes, ensure efficient energy use and prevent problems such as overcharging. In addition, the system provides real-time data and diagnostics to facilitate effective battery health management.

Flood Detection System Using Data Fusion Technique for IoT

2024-04-16T10:10:56+00:00

Flood is a natural phenomenon that also occurs by a manmade pollution to cause climatic changes. They can result from heavy rainfall, snowmelt, storm surges, or the overflow of rivers and dams. Flood causes significant losses to people's lifestyles, as well as disrupt ecosystems and economies. Prevention and early warning systems are crucial for minimizing the impact of floods on communities. Flood detection involves using various technologies like sensors, satellite imagery, and machine learning algorithms to monitor water levels and detect anomalies indicative of flooding to provide early warnings and minimize damage. During floods, communities face property damage, loss of life, and displacement due to evacuation. Infrastructure damage disrupts rescue efforts and essential services, while health risks from contaminated water pose additional threats to affected populations. Economic impacts can be significant, requiring long-term recovery efforts to rebuild and restore affected areas. The existing system contains only monitoring the temperature, and humidity that is prediction based machine learning algorithms. To overcome this problem we proposed getting the required information for every individual who is staying in the particular zone. It is an easy communication between technology and people. To get sufficient details every individual can set their safety detection technique through mobile phones.