The deadly virus COVID-19 has heavily impacted all countries and brought a dramatic loss of human life. It is an unprecedented scenario and poses an extreme challenge to the healthcare sector. The disruption to society and the economy is devastating, causing millions of people to live in poverty. Most citizens live in exceptional hardship and are exposed to the contagious virus while being vulnerable due to the inaccessibility of quality healthcare services. This study introduces ubiquitous computing as a state-of-the-art method to mitigate the spread of COVID-19 and spare more ICU beds for those truly needed. Ubiquitous computing offers a great solution with the concept of being accessible anywhere and anytime. As COVID-19 is highly complicated and unpredictable, people infected with COVID-19 may be unaware and still live on with their life. This resulted in the spread of COVID-19 being uncontrollable. Therefore, it is essential to identify the COVID-19 infection early, not only because of the mitigation of spread but also for optimal treatment. This way, the concept of wearable sensors to collect health information and use it as an input to feed into machine learning to determine COVID-19 infection or COVID-19 status monitoring is introduced in this study.

Flood disaster is known to impact people and the environment substantially. People impacted by floods may lose properties and homes. Furthermore, there are also a substantial number of deaths yearly in case of a flood disaster. Malaysia has been hit by floods pretty frequently for the past few years. Government bodies and non-government organisations have collaborated to develop necessary measures to mitigate the flood disaster. Flood forecasting, warning, and zoning have been acknowledged as some of the few non-structural strategies considered crucial in flood mitigation. All these measures are vital to reduce the impact of the flood disaster on the people, eventually making them prepared to embrace any emergency. Technology is believed to play an essential role in tackling the flood issue. Several countries all across the globe have relied on the current advancements in technology to make predictions regarding flood incidents, weather forecasting and so on. Moreover, these systems give warnings and alerts to the people before a flood disaster. Therefore, utilising technology in tackling disasters like floods can reduce the severe impacts of floods in the years to come and also tends to end the loss of lives due to floods. As part of this research, the authors have first investigated the requirements and then proposed the design of a simple and easy-to-implement IoT-based flood monitoring system. Finally, a prototype is prepared to provide the proof of concept of the proposed solution.

Surveillance camera has become an essential, ubiquitous technology in people's daily lives, whether applicable for home surveillance or extended to public workplace detection. The importance of the camera is irreplaceable in terms of the agent for an enclosed system to function correctly. The goal of ubiquitous computing is to keep different devices or technology communicating seamlessly, allowing them to expand to other areas instead of limiting it to one device. However, many research papers have been released on how the camera can aid in the current situation where COVID-19 is still raging worldwide, especially in crowded places. This paper aims to suggest a method by which surveillance cameras on the university campus can automatically detect student face mask status and notify them. Alongside that, this concept of applying a video management system within the university campus will assist in the automation of invigilating the student's daily mask status from the number of embedded surveillance cameras around the campus.

This research proposes a smart entrance system to cope with the COVID-19 pandemic in public places. The system can help automate standard operating procedures (SOPs) for checking. The paper focuses on exploring the problem context related to the COVID-19 SOPs for public places. The research on technologies involves using thermal cameras, fingerprint recognition, face recognition, iris recognition, object detection and cloud computing. These technologies can be integrated to provide a more versatile and effective solution. The technological solutions proposed by contemporary researchers are also critically analysed by investigating their advantages and disadvantages.

Streetlights are among the essential public infrastructure components for both urban and rural areas. It allows people to provide a clear vision at night and brings convenience to society. A Smart Street Lighting System uses IoT sensors and can interact with software to improve its effectiveness and utility. Since streetlights must be turned on for the entire duration of the night, it is essential to find ways of reducing energy consumption to actualize a greener society. It can be done by integrating sensors that can detect movements and control the way streetlights behave through the gathered data. This research aims to reduce the energy consumption needed for the operation of streetlights by applying appropriate IoT based techniques. An extensive discussion on the existing literature and similar systems reviews the current developments critically. The research gathered public insights through a quantitative research approach and applied this information in recommending a solution. With the help of a prototyping model, the authors demonstrated how a Smart Street Lighting System could achieve optimal performance.

In the current era of globalisation, water pollution has gradually worsened, and it has started to reach alarming heights. Water pollution has a severe impact on human health and the environment. The rationale of this research is to propose an affordable water quality monitoring system to save and conserve the quality of consumed water. Water conservation is among the most critical segments of a future smart city project that many countries strive to achieve. This research investigates Malaysia's current water pollution situation and reviews the existing policies that the government has already implemented to curb this issue. Furthermore, it provides an in-depth analysis of similar systems that other fellow researchers have presented. In this paper, the authors have proposed an enhanced water quality monitoring system by implementing an IoT based technological infrastructure suitable for a smart city project. The proposed approach provides a low-cost and power-saving alternative to commercially available systems.