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Fire is the fundamental element of most people’s lives, and when not controlled, the same fire can lead to several catastrophes in homes, offices, schools, lives and other public places with severe repercussions. Hence, this study aims to examine the adequacy and extent of the application of fire suppression systems in residential and commercial property in Ghana.

This study adopts a sequential mixed-mode design comprising quantitative and qualitative research strategies to analyse factors to produce findings. The target population for this study includes shop occupiers, end users of office buildings, and residents in the Accra Central of Ghana. Systematic random sampling was used for the quantitative research, and a sample size of 385 was obtained using a multi-stage and cluster sampling method. A structured survey and semi-structured interviews were used to collect the primary data. The quantitative data were analysed using descriptive and inferential statistics, whereas the qualitative data were analysed using content analysis.

From an empirical literature review and the analysis, the three main factors contributing to fire breakouts are equipment malfunction, improper use of heat sources and human mistakes. According to the respondents, fire suppression systems were also inadequate, as most of the suppression systems prescribed in the building code were unavailable. Regarding the ability to manually operate fire suppression systems, most property occupiers stated that they are generally unaware of these suppression systems.

This study will aid policymakers in developing interventions for fire safety enforcement by ensuring that fire safety regulations are consistently followed by design team members and property developers, resulting in a positive effect on public building structures performing their required functions. It is also critical to provide end users with education and training on how to operate the fire suppression system as well as effective handling of firefighting installations in the event of a fire.

The findings of this investigation contribute to knowledge and comprehension of the effect of fire suppression systems on building users and may serve as a precursor to the development of a “As Built” certification system for ascertaining the adequacy of fire suppression systems for new and existing residential and commercial property.

The statistics show that older adults have been major fire victims in high-rise buildings. However, the fire safety building codes in most countries are not inclusive and do not reflect provisions for older adults. The research aims to develop a fire risk assessment index system for older adults living in high-rise residential buildings in India. The study further develops a fire rating system to improve fire safety provisions in high-rise buildings in India.

The paper employs Delphi, analytic hierarchy process (AHP) and fuzzy comprehensive risk evaluation techniques. It considers 18 in-depth interviews and group discussions with builders, developers, architects, policymakers, and fire safety experts and consultants to develop a fire risk assessment system for older occupants living in high-rise residential buildings in India.

The fire protection systems and fire management systems are not as per the needs of older adults. The egress system components need improvisation considering the challenges of older adults.

The study is limited to older adults living in high-rise residential buildings in the capital city of Gujarat, Ahmedabad.

This study will assist policymakers in developing fire safety standards that are targeted to the needs of older persons living in high-rise residential buildings during a fire evacuation.

While several approaches for measuring fire risk in high-rise residential buildings exist, no such system has been developed specifically for older adults in India.

Community centers play a socio-economic and urban role of combining different communal necessities, that serve inhabitants, at different neighborhoods in cities. Their role emerged in importance as being a hub for improving and customizing quality of life experiences of the public. This research presents a code-based risk assessment tool for evaluating fire safety measures that can be adapted in the context of community centers. It also provides an exemplary case study to demonstrate its application.

The study identified the factors that render community centers as a high-risk type of facilities in fire events. Various fire codes and standards were reviewed to describe the relevant fire safety measures. A code-based fire risk assessment tool was developed and implemented, through a case study. A set of recommendations were developed to improve the fire safety conditions of the case study facility.

Several violations to fire safety were identified in the case study building. The findings led to identifying a set of recommendations to improve its fire safety conditions.

This research introduced a systematic approach to raise awareness about fire incidences and consequences in community centers, and provides facilities managers with a tool, to assess compliance based on international fire code requirements.

In fire events, community centers are considered as high-risk facilities that may lead to significant losses of human lives and damages to assets. It is significant to study the causes of fire, for ensuring effective prevention and safe operations.

The extreme nature of fire makes structural fire engineering unique in that the load actions dictating design are intense and neither geographically nor seasonally bound. Simply, fire can break out anywhere, at any time and for any number of reasons. Despite the apparent need, the fire design of structures still relies on expensive fire tests, complex finite element simulations and outdated procedures with little room for innovation. This paper aims to discuss the aforementioned issues.

This primer highlights the latest state of the art in this area with regard to performance-based design in fire structural engineering. In addition, this short review also presents a series of examples of successful implementation of performance-based fire design of structures from around the world.

A comparison between global efforts clearly shows the advances put forth by European and Oceanian efforts as opposed to the rest of the world. In addition, it can be clearly seen that most performance-based fire designs are related to steel and composite structures.

In one study, this paper presents a concise and global view to performance-based fire design of structures from success stories from around the world.

Effective facility management (FM) can reduce environmental effects on buildings throughout their life cycle. This study aims to investigate the challenges in implementing building information modelling (BIM) for FM in government buildings in Thailand.

Eight government-building facility experts were interviewed using an in-depth interview method to identify FM challenges. The collected qualitative data were analysed via thematic analysis to ensure data saturation. The final questionnaire was designed with 45 FM problems, classified into management, technical and human resource problems, to collect quantitative data from 54 government FM officers. The data were used to prioritise the severity and frequency of the FM problems using the severity index (SI) and relative importance index (RII).

Management problems have the highest impact, with an average SI of 0.285, followed by human resource (average SI = 0.266) and technical (average SI = 0.264) problems.

This study identifies the government-building FM problems in Thailand that are critical to the development of a BIM execution plan (BEP) guideline. The findings can facilitate strategy development for government-building operations and management in line with the public procurement and supply administration of Thailand. These findings can serve as a guideline to inform the development of a BIM Roadmap for integration into the national digital roadmap and the Thailand 4.0 policy to mitigate construction-related environmental and climate issues.

This study aims to explore occupants’ perceived importance and satisfaction with high-rise students’ housing facilities’ fire safety considerations (FSCs). The specific objectives are to explore the FSCs for high-rise students’ housing facilities and assess the level of importance and satisfaction with the FSCs provided in high-rise students’ housing facilities in controlling fire outbreaks.

The study uses an exploratory sequential design with an initial qualitative phase followed by a quantitative data collection phase. Twenty FSCs were identified through the qualitative phase via semistructured interviews. Their importance and satisfaction were revealed through survey questionnaires with 168 respondents who stayed in or were involved in the operation of high-rise students’ housing facilities. Data from the qualitative phase were analyzed thematically, and those obtained from the quantitative phase were analyzed descriptively and inferentially.

The study’s findings revealed that all the 20 FSCs identified via the qualitative phase and confirmed through the quantitative phase were perceived to be very important in fighting fires in high-rise students’ housing facilities. However, only 9 out of the 20 FSCs received some satisfaction among the respondents in fighting fires in the facilities.

This study offers insight into a rare study area, especially in sub-Saharan Africa. In addition, it grants insight into the occupants’ perspective regarding which FSCs they consider essential and their level of satisfaction with such FSCs in fighting fires in high-rise students’ housing facilities.

The creation of occupant satisfaction can be reached through the involvement of building performance mandates (BPMs) while enhancing the functionality of buildings. BPMs comprise five mandates namely, spatial performance, thermal performance, indoor air quality performance, acoustic performance, and visual performance. BPMs have been recognized as a vital element when refurbishing post-fire apparel buildings. However, the evaluation of post-fire refurbishment projects is mainly focused on mechanical and physical properties while ignoring the BPMs. Further, there is insufficient literature on the BPMs in post-fire building refurbishment. Hence, the purpose of this research is to identify the importance of BPMs, and its challenges and propose strategies to enhance the building performance of post-fire refurbished apparel manufacturing buildings in Sri Lanka.

The study was conducted by involving a qualitative research approach. An extensive literature review and eighteen semi-structured interviews under three fire-affected apparel cases were involved as data collection methods and collected data were analyzed using content analysis.

Findings highlighted the procedure of post-fire refurbishment and the importance of BPMs for apparel buildings to enhance building performance in post-fire situations. The research identified 42 challenges encountered in maintaining BPMs of post-fire refurbished apparel buildings and provided 70 strategies to overcome the identified challenges.

This study offers a comprehensive analysis of challenges in maintaining BPMs and strategies to overcome the identified challenges which facilitate enhancing the performance of post-fire refurbished apparel buildings in Sri Lanka.

The fire sector within the United Kingdom has identified a need to further develop their systematic use of academic literature and develop mechanisms to include academic knowledge to inform evidence-based policy and practice. By increasing knowledge exchange between the fire sector and academia, the ability to horizon scan and identify future relevant phenomena of interest to the fire sector will be achieved. Consequently, the evidence base and horizon scanning will increase the specificity of techniques, approaches and practices needed to continually improve the safety of the activities completed within the firefighting occupation, and it will also provide priority areas for investment and increase firefighter safety.

This technical paper primarily features an initial scoping review of academic and grey literature and an operational incident data review. This was completed to provide an initial and updated review of disciplines and areas of academia that are actively engaged in research relevant to the fire and rescue service. Consequently, this method sought to identify and examine the various disciplines of academia involved in fire research. This paper then uses that outcome to suggest a model of multidisciplinarity to inform the fire sector.

As a result of the scoping review, each academic discipline was identified and an initial review developed a predetermined set of key search terms. This was established through identifying the most frequently used fire-related terms within each discipline. This allowed for a comprehensive understanding of the breadth of activity and depth of complexity of fire related research within each discipline and an indicative set of key search terms to be developed. Recommendations are formulated to suggest next steps to routinely incorporate the academic knowledge base in the learning process of the fire and rescue services in the United Kingdom.

This paper provides an initial scoping map of academic literature and disciplines relevant to activities completed in the UK fire sector, which can be used to further develop the evidence base to inform the fire and rescue service of the United Kingdom. It also outlines possible mechanisms and a model to systematically facilitate knowledge exchange between academia and the fire sector by which knowledge exchange could further support the development of evidence-based policy and practice. The broad range of benefits of collaboration between the fire and rescue service and academia are explored.

This paper provides clear evidence as to why fire related research should have an increased priority status to inform the national fire and rescue services learning process and evidence for national policy and guidance development within the UK fire and rescue service. Additionally, recommendations are made to support the consideration of academic evidence in the systematic sector wide learning process.

Previously, the UK fire and rescue service had limited coordinated strategic engagement with academic disciplines to further develop their learning processes in order to produce an evidence base, which is cognisant of academic research to inform practice and guidance. This paper begins the narrowing of that gap by categorising academic literature relevant to fire research into clear disciplines, mapping these to an updated breadth of current activities undertaken by the fire and rescue service across the United Kingdom. The process also details a pilot of the proposed model to support knowledge exchange by producing an academically evidence-based submission to the National Fire Chiefs Council organisational learning process.

This study aims to design a compact filtering monopole antenna for 5G communication. The design is most suited for various applications within the frequency range of 2.2–3.8 GHz. It offers enhanced bandwidth and reasonable gain with wide-stopband performance.

A low-pass filter (LPF) of complementary split ring resonator (CSRR) with short-circuited stub lines is integrated with a compact defected coplanar waveguide fed truncated circular monopole ultrawideband (UWB) antenna. The reference UWB antenna etched on an FR4 substrate was coupled to the designed LPF to transform the UWB antenna into a wideband antenna. The effect of coupling is analyzed based on the real and imaginary responses of the terminal impedance (ZT) curve. Three short-circuited stub lines of asymmetric lengths are added to the CSRR LPF to suppress harmonics, thereby enhancing the stopband performance and impedance matching between the elements. The proposed filtering antenna is fabricated using a photolithography process, and the corresponding results are measured using a network analyzer (N9951A). The radiation parameters of the proposed filtering monopole antenna are tested in the anechoic chamber. The simulated/measured results are compared and are found in agreement with each other.

The proposed design suppresses 6.5f0 harmonics, resulting in wide stopband performance and increased gain selectivity at the transition edge. A peak suppression of −41 dB and an average suppression of −18 dB were attained throughout the stopband. An operating fractional bandwidth of 54.5%/143% with a peak gain of 3 dBi/5 dBi was obtained. The proposed filtering antenna supports 5G applications such as WiMAX, WLAN, n7, n38 IMT-E, n30 WCS, n40 TDD, n41 TDD, n48 TDD, n78 TDD and n90 TDD.

The proposed design is novel and compact and has a wide application in 5G communication. With the filter, the antenna operates in wideband, and without the filter, it operates in UWB. Besides, it offers enhanced stopband performance with high gain selectivity at the transition edge. Comparatively, a 50% improvement in bandwidth, 52% improvement in size reduction and 33% improvement in harmonic suppression are attained.

This paper aims to implement and extend the You Only Live Once (YOLO) algorithm for detection of objects and activities. The advantage of YOLO is that it only runs a neural network once to detect the objects in an image, which is why it is powerful and fast. Cameras are found at many different crossroads and locations, but video processing of the feed through an object detection algorithm allows determining and tracking what is captured. Video Surveillance has many applications such as Car Tracking and tracking of people related to crime prevention. This paper provides exhaustive comparison between the existing methods and proposed method. Proposed method is found to have highest object detection accuracy.

The goal of this research is to develop a deep learning framework to automate the task of analyzing video footage through object detection in images. This framework processes video feed or image frames from CCTV, webcam or a DroidCam, which allows the camera in a mobile phone to be used as a webcam for a laptop. The object detection algorithm, with its model trained on a large data set of images, is able to load in each image given as an input, process the image and determine the categories of the matching objects that it finds. As a proof of concept, this research demonstrates the algorithm on images of several different objects. This research implements and extends the YOLO algorithm for detection of objects and activities. The advantage of YOLO is that it only runs a neural network once to detect the objects in an image, which is why it is powerful and fast. Cameras are found at many different crossroads and locations, but video processing of the feed through an object detection algorithm allows determining and tracking what is captured. For video surveillance of traffic cameras, this has many applications, such as car tracking and person tracking for crime prevention. In this research, the implemented algorithm with the proposed methodology is compared against several different prior existing methods in literature. The proposed method was found to have the highest object detection accuracy for object detection and activity recognition, better than other existing methods.

The results indicate that the proposed deep learning–based model can be implemented in real-time for object detection and activity recognition. The added features of car crash detection, fall detection and social distancing detection can be used to implement a real-time video surveillance system that can help save lives and protect people. Such a real-time video surveillance system could be installed at street and traffic cameras and in CCTV systems. When this system would detect a car crash or a fatal human or pedestrian fall with injury, it can be programmed to send automatic messages to the nearest local police, emergency and fire stations. When this system would detect a social distancing violation, it can be programmed to inform the local authorities or sound an alarm with a warning message to alert the public to maintain their distance and avoid spreading their aerosol particles that may cause the spread of viruses, including the COVID-19 virus.

This paper proposes an improved and augmented version of the YOLOv3 model that has been extended to perform activity recognition, such as car crash detection, human fall detection and social distancing detection. The proposed model is based on a deep learning convolutional neural network model used to detect objects in images. The model is trained using the widely used and publicly available Common Objects in Context data set. The proposed model, being an extension of YOLO, can be implemented for real-time object and activity recognition. The proposed model had higher accuracies for both large-scale and all-scale object detection. This proposed model also exceeded all the other previous methods that were compared in extending and augmenting the object detection to activity recognition. The proposed model resulted in the highest accuracy for car crash detection, fall detection and social distancing detection.