Next generation wireless networks for social good

Abstract

The advancement of technology and communication systems has yielded beneficial outcomes in everyday life. Including next generation wireless networks is an integral component of this evolutionary process. Consequently, the advancement of technology and evolving needs have led to the enhancement of wireless communication systems by implementing next generation wireless networks, thereby rendering them more powerful and efficient. These technologies, such as mobile communications, industrial applications, and the Internet of Things (IoT), significantly impact our lives. In addition to the factors above, wireless networks have emerged as a pivotal tool in addressing societal challenges. Next generation wireless networks have the potential to manage various critical domains such as natural disasters, environmental concerns, traffic and transportation challenges, and public health issues. Because of these reasons , this thesis has two main objective utilizing wireless networks. Firstly, we propose a wildfire monitoring method. Wildfires have emerged as a significant worldwide concern in today's world. The prevalence and severity of wildfires have increased due to climate change, anthropogenic actions, and natural influences. In response to the prevailing ecological crisis, researchers and professionals in science and engineering are actively exploring a range of technological and supplementary precautions. The findings of this investigation indicate that unmanned aerial vehicles (UAVs) significantly impact combatting forest fires. UAVs have become essential tools in firefighting and monitoring operations due to their notable attributes, including user-friendly interfaces, exceptional maneuvering capabilities, and enhanced availability. Nevertheless, the constrained energy capacity of a singular UAV poses a significant challenge in efficiently surveilling expansive fire zones. To effectively tackle these challenges and enhance the efficiency of firefighting operations, a proposed solution is implementing an advanced monitoring application called "Phoenix." Phoenix provides an advanced fire-tracking monitoring system, which integrates path planning, a graph engine, and modified Traveling Salesman Problem (TSP) algorithms. This system aids the UAV in effectively tracking fire areas and optimizing its trajectory. This capability enables the UAV to conduct a more efficient scanning of the fire area, reducing response time. Consequently, this helps to mitigate the spread of the fire. Phoenix has designed a network architecture that facilitates the prompt transmission of monitoring data to the fire brigade and other firefighting units. This enables the firefighting crews to remain informed about the prevailing conditions at the site and enhance their coordination efforts.The Phoenix application facilitates energy optimization to tackle the energy limitations an individual Unmanned Aerial Vehicle (UAV) faces. Therefore, UAVs can remain airborne for an extended duration and effectively survey more significant geographical regions. This enhances the efficacy of firefighting operations. The application operates by employing elliptical fire modeling and simulation techniques. Additionally, the analysis of critical fire zones incorporates fuel moisture content (fmc) data within the fire zone. This facilitates Phoenix's enhanced ability to respond effectively to real-world situations, thereby augmenting the likelihood of success in firefighting endeavors. Secondly, we propose a blind spot detection method to protect pedestrians, cyclists and motorcyclists in traffic and prevent accidents. Traffic crashes are a significant issue that regrettably results in numerous fatalities and injuries in contemporary times. Traffic accidents are a prominent contributor to global mortality rates, particularly in middle-income nations with high traffic volumes and insufficient or inadequate infrastructure. Despite implementing numerous safety measures to address this issue, a significant level of risk remains, particularly for susceptible road users, including pedestrians, cyclists, and motorcyclists. The significance of vehicle blind spots is a crucial factor in such accidents. Despite the recent introduction of advanced safety systems incorporating costly hardware, detecting vulnerable users remains challenging, particularly in situations where the field of view is obstructed. Furthermore, we utilized ultra-wide-band (UWB) technology to develop this system. UWB is an advantageous wireless communication tool for both cost-effectiveness and widespread availability. We use the Time Difference Of Arrival (TDOA) method to detect the vehicle or pedestrian in the blind spot. We have developed a demo by developing this proposed method. We used four UWB kits and a UWB-supported mobile phone for this demo. We implement the software in the kits used for the demo and the software of the application on the mobile phone ourselves. Apart from that, we compared our method with different methods using simulation. In conclusion, this thesis proposes two next-generation wireless network approaches. First, Phoenix, an advanced monitoring program, powers the suggested wildfire monitoring technique. This novel technology uses UAVs, advanced algorithms, and fire model to revolutionize firefighting, save lives, preserve ecosystems, and reduce wildfire damage. Phoenix shows how technology can safeguard our environment and develop a more resilient and sustainable future as we battle climate change and wildfires. The second stage of this thesis proposes and examines the continuing development and enhancement of road safety technology like blind spot identification, which reduces traffic accidents and saves lives. UWB technology and new algorithms may make roads safer and more inclusive. These road safety applications use technology, legislation, and public awareness to reduce accidents and make roads safer.