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This paper aims to illustrate the growing role of drones in applications involving physical tasks.

Following a short introduction, this first provides a brief introduction to drone technology. It then describes and discusses products and applications involving physical tasks in agricultural and forestry, maritime rescue, firefighting and product delivery. Finally, brief conclusions are drawn.

Excluding military applications, drones were initially used primarily for image acquisition. Numerous different designs have since been developed with greatly varying wing configurations, payloads, flight duration, power sources and other features which are increasingly being used to conduct physical tasks. In the applications considered here drones are applying agrochemicals and dispersing crop and tree seeds; saving lives by deploying lifeboats and buoyancy aids; extinguishing fires in high-rise buildings and forests; and delivering groceries, food, mail, medicines and humanitarian aid, often in and to remote locations.

This study provides a detailed insight into selection of applications in which drones conduct physical tasks.

Achieving tenure security is a global challenge impacting cities of the global south. The purpose of this paper is to evaluate the role of technology-enabled solutions as an enabler for the tenure rights of slum dwellers.

In this paper, we adopted a case study approach to analyze the use cases for technologies aiding India’s securitization of land tenure. The flagship state mission of Odisha, named the Jaga Mission, and that of Punjab, named BASERA – the Chief Minister’s Slum Development Program – were used as cases for this paper.

It was found that technologies like drone imagery and digital surveys fast-tracked the data collection and helped in mapping the slums with accuracy, mitigating human errors arising during measurement – a necessary condition for ensuring de jure tenure security. The adoption of a technology-based solution, along with a suitable policy and legal framework, has helped in the distribution of secure land titles to the slum dwellers in these states.

Odisha’s and Punjab’s journey in using technology to enable tenure security for its urban poor residents can serve as a model for the cities of the global south, dealing with the challenges of providing secure tenure and property rights.

The purpose of this study is to evaluate food supply chain stakeholders’ intention to use Industry 5.0 (I5.0) drones for cleaner production in food supply chains.

The authors used a quantitative research design and collected data using an online survey administered to a sample of 264 food supply chain stakeholders in Nigeria. The partial least square structural equation model was conducted to assess the research’s hypothesised relationships.

The authors provide empirical evidence to support the contributions of I5.0 drones for cleaner production. The findings showed that food supply chain stakeholders are more concerned with the use of I5.0 drones in specific operations, such as reducing plant diseases, which invariably enhances cleaner production. However, there is less inclination to drone adoption if the aim was pollution reduction, predicting seasonal output and addressing workers’ health and safety challenges. The findings outline the need for awareness to promote the use of drones for addressing workers’ hazard challenges and knowledge transfer on the potentials of I5.0 in emerging economies.

To the best of the authors’ knowledge, this study is the first to address I5.0 drones’ adoption using a sustainability model. The authors contribute to existing literature by extending the sustainability model to identify the contributions of drone use in promoting cleaner production through addressing specific system operations. This study addresses the gap by augmenting a sustainability model, suggesting that technology adoption for sustainability is motivated by curbing challenges categorised as drivers and mediators.

Observation of the animal world is an important component of nature surveys. It provides a number of different information concerning aspects such as population sizes, migration directions, feeding sites and many other data. The paper below presents the results from the flights of an unmanned aerial vehicle (UAV) aimed at detecting animals in their natural environment.

The drone used in the research was equipped with RGB and thermal infrared (TIR) cameras. Both cameras, which were mounted on the UAV, were used to take pictures showing the concentration of animals (deer). The overview flights were carried out in the villages of Podlaskie Voivodeship: Szerokie Laki, Bialousy and Sloja. Research flights were made in Bialousy and Sloja. A concentration of deer was photographed during research flights in Sloja. A Durango unmanned platform, equipped with a thermal imaging camera and a Canon RGB camera, was used for research flights. The pictures taken during the flights were used to create orthomaps. A multicopter, equipped with a GoPro camera, was used for overview flights to film the flight locations. A flight control station was also used, consisting of a laptop with MissionPlanner software.

Analysis of the collected images has indicated that environmental, organisational and technical factors influence the quality of the information. Sophisticated observation precision is ensured by the use of high-resolution RGB and TIR cameras. A proper platform for the cameras is an UAV provided with advanced positioning systems, which makes it possible to create high-quality orthomaps of the area. When observing animals, the time of day (temperature contrast), year season (leaf ascent) or flight parameters is important.

The paper introduces the conclusions of the research flights, pointing out useful information for animal observation using UAVs.

To critically assess the reconstruction process's outcomes four months after a wildfire disaster in Viña del Mar, Chile, comparing the governmental reconstruction plan and the actual rebuilding efforts by the dwellers.

A geographic information system (GIS)-based analysis to deliver a spatial-based comparison of (1) the cadastre of damaged dwellings; (2) the Ministry of Housing and Urbanism’s (MINVU) reconstruction plan and (3) the actual reconstruction that has been carried out by the dwellers themselves up to November 2023 (as surveyed through fieldwork and drone flights).

Around 307 dwellings (97.7% of the 314 examined households) had been rebuilt by November 2023, all through the dwellers’ self-reconstruction efforts, except for two houses delivered by MINVU. Around 105 of these dwellings (34.2%) were granted a reconstruction subsidy by MINVU, while 155 (49.4% of the sample of 314 dwellings) were rebuilt without this aid. Also, 47 houses were rebuilt by dwellers in areas deemed “non-rebuildable” due to their high-risk levels.

We use a mixed-methods approach to examine disruptions between planned reconstruction and actual rebuilding processes following a wildfire disaster in areas with significant informality.

Global construction sector studies have significantly explored the impact of automation techniques, revealing their transformative potential. However, research on their application within specific local contexts, especially in developing countries like Nigeria, is sparse. Nigeria presents a unique context marked by challenges such as skilled labor shortage, safety concerns and cost efficiency. Therefore, investigating the implementation of automation techniques in the Nigerian construction industry is crucial to address these challenges, bring transformative advancements and contribute to a more balanced global discourse on automation adoption. This study aims to fill this significant research gap.

A mixed research method was deployed which combined both qualitative and quantitative data collection and analysis. Two focus group discussions conducted with 23 experts from both industry and academic institutions (qualitative) yielded 17 drivers which were used to formulate a well-structured questionnaire (quantitative), which was disseminated to construction professionals. Collected data underwent analysis through various statistical techniques, including percentages, frequencies, mean item scores and exploratory factor analysis.

Principal component analysis (PCA) yielded four driver clusters namely: (1) performance-related drivers, (2) visualization and efficiency-related drivers, (3) technological and human-related drivers and (4) economic-related drivers.

The study provides empirical insights that can aid stakeholders, decision-makers, policymakers and the government in formulating strategies to promote automation techniques in the Nigerian construction industry and beyond.

This study's originality lies in its exploration of the untapped potential of automation techniques in the Nigerian construction industry, offering novel perspectives on how these technologies can address specific challenges such as skilled labor shortage, safety concerns and cost efficiency, thereby paving the way for transformative advancements in the sector.

The age of artificial intelligence (AI) is already upon us. The rapid development of AI tools is facilitating sustainable development and its corollary social good. For AI dedicated to social good to be impactful, it has to be human-centred, striving to achieve inclusiveness, sustainable livelihoods and community well-being. In short, it offers major opportunities to holistically enhance peoples' lives in diverse areas: education, health care, food security, disaster reduction, smart cities, etc. However, ethical, unbiased and ‘secure-by-design’ algorithms that power AI are crucial to building trust in this technology. Civil society's engagement can hopefully drive the features and values that should be embedded in AI.

This chapter focuses on the societal benefits that AI can deliver. Our initiatives and decisions of today will fashion the ‘Social Good’ AI applications of tomorrow. Sustainable Development Goals (SDGs) being addressed are 2–4 and 10–11.

This study aims to quantify and analyse the dynamics of land use and land cover (LULC) changes over three decades in the rapidly urbanizing city of Abha, Saudi Arabia, and to assess urban growth using Morphological Spatial Pattern Analysis (MSPA).

Using the Support Vector Machine (SVM) classification in Google Earth Engine, changes in land use in Abha between 1990 and 2020 are accurately assessed. This method leverages cloud computing to enhance the efficiency and accuracy of big data analysis. Additionally, MSPA was employed in Google Colab to analyse urban growth patterns.

The study demonstrates significant expansion of urban areas in Abha, growing from 62.46 km² in 1990 to 271.45 km² in 2020, while aquatic habitats decreased from 1.36 km² to 0.52 km². MSPA revealed a notable increase in urban core areas from 41.66 km² in 2001 to 194.97 km² in 2021, showcasing the nuanced dynamics of urban sprawl and densification.

The novelty of this study lies in its integrated approach, combining LULC and MSPA analyses within a cloud computing framework to capture the dynamics of city and environment. The insights from this study are poised to influence policy and planning decisions, particularly in fostering sustainable urban environments that accommodate growth while preserving natural habitats. This approach is crucial for devising strategies that can adapt to and mitigate the environmental impacts of urban expansion.

The purpose of this article was to identify and evaluate the benefits of adopting digital technologies (DTs) in the Nigerian construction industry, to ensure that construction projects are efficiently and effectively executed.

A scoping literature review was conducted through which benefits of implementing DTs were identified, which helped in the formulation of a questionnaire survey. Data were obtained from construction professionals including architects, builders, engineers and quantity surveyors. Retrieved data were analyzed using several statistical tools such as percentages, frequencies, mean item scores and exploratory factor analyses.

Based on the mean item score ranking results, the top five significant benefits of adopting DTs were increased operational efficiency, increased productivity, increased speed of executing tasks, seamless working methodology and accurate documentation of data. Findings from the factor analysis revealed six clusters of benefits namely an improved framework for operations, improved innovativeness, improved safety practices, increased competitive edge, greater accuracy and increased productivity.

This study expands on the existing discussions surrounding the digital transformation of the construction sector in developing countries, particularly in Nigeria, a region where the awareness and implementation of smart and innovative technologies are still at an infant stage.

Although several studies on the benefits of adopting DTs in the construction industry of developing countries exist, very few have been conducted in the Nigerian context. Thus, this is a significant knowledge gap that must be filled. Thus, the findings of this study can serve as a basis for construction organizations in Nigeria and similar countries seeking the digital transformation of their activities.

The main purpose of the study was mechanical designing, simulation and manufacturing process for a new model of octocopter V-frame and to achieve simple manufacturing with 3D printing technology. Moreover, the octocopter PID controller was simulated on the Simulink environment to get performance on the roll and pitch angle control.

Octocopter is one kind of multirotor vehicle (a rotorcraft with more than two rotors), that has lately gained a lot of attention for both the scientific and commercial spheres. With a greater number of rotors, the multirotor is very maneuverable and robust. Multi-copter makes an important contribution to the technological revolution in the military, industry, transportation, mapping and especially agriculture. Nowadays, we are heading to the four-industrial revolutions as well as the new technological application in the agricultural field such as precision agriculture, mapping and surveillance. Due to recently advanced technology about sensors, electronics, 3D printing, battery with high performance, multi-copter can be manufactured at low cost.

The V-frame octocopter was chosen to design in this paper; it had better performance scores including high redundancy rotors, high payload capability and affordable cost than another multi-copter family. The V-frame octocopter increasing freedom field of view of the camera was considered to place the camera position in the front of the drone.

For the future aspects, the mechanical structure of the octocopter could be improved by using more advanced metal 3D printing to produce the aluminum or titan alloy materials for lighter and more rigid compared with ABS material, and finally the assembly to the real test.

The study shows the new platform of the V-frame octocopter kinematics analysis, designed on the CAD software, with some important mechanical parts using FEM analysis to find the highest stress and displacement under high load applied, the result of all connecting the joints 3D printing part is completely safe. Mechanical parts were manufactured by using 3D printing technology and CNC milling. Moreover, the study has shown V-frame octocopter simulation based on Simulink using the second method Ziegler- Nichols to find suitable parameters of the PID controller for roll and pitch angle. Using the block simulation is good for implementing and fast checking the new algorithm when building the new platform of the robot.