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The purpose of this study is to offer a better and more effective hexacopter design for a 3 kg payload using finite element analysis (FEA), facilitating the use of different materials for different components that too without compromising strength.

A 3D computer-aided design (CAD) model of a hexacopter with a regular hexagonal frame is presented. Furthermore, a finite element model is developed to perform a structural analysis and determine Von Mises stress and strain values along with deformations of different components of the proposed hexacopter design.

The results establish that carbon fibre outperforms acrylonitrile butadiene (ABS) with respect to deformations. Within the permissible limits of the stress and strain values, both carbon fiber and ABS are suggested for different components. Thus, a proposed hexacopter offers lighter weight, high strength and low cost.

The use of different materials for different components is suggested by making use of static structural analysis. This encourages new research work and helps in developing new applications of hexacopter, and it has never been reported in literature. The suggested materials for the components of the hexacopter will prove to be suitable considering weight, strength and cost.

This study aims to assess the spread of environmental literacy graduation requirements at public universities in the USA, and to highlight factors that mediate the adoption of this curriculum innovation.

The author analyzed the undergraduate general education curriculum requirements at all 549 public BA-granting higher education institutions in the USA between 2020 and 2022.

The study found that only 27 US public universities out of 540 have an environmental literacy graduation requirement, which represents 5% of universities and is substantially lower than previous estimates.

First, this study provides a more complete, more reliable and more current assessment of the graduation requirement’s presence at US tertiary institutions, and shows the number of universities that have implemented this innovation is lower than was estimated a decade ago. Second, it draws from the scholarship on the infusion of sustainability into the university curriculum to provide a comprehensive discussion of factors that mediate the pursuit and implementation of the graduation requirement. As well, it identifies factors that played a key role in one pertinent case.

Nowadays, food problems are likely to arise because of the increasing global population and decreasing arable land. Therefore, it is necessary to increase the yield of agricultural products. Pesticides can be used to improve agricultural land products. This study aims to make the spraying of cherry trees more effective and efficient with the designed artificial intelligence (AI)-based agricultural unmanned aerial vehicle (UAV).

Two approaches have been adopted for the AI-based detection of cherry trees: In approach 1, YOLOv5, YOLOv7 and YOLOv8 models are trained with 70, 100 and 150 epochs. In Approach 2, a new method is proposed to improve the performance metrics obtained in Approach 1. Gaussian, wavelet transform (WT) and Histogram Equalization (HE) preprocessing techniques were applied to the generated data set in Approach 2. The best-performing models in Approach 1 and Approach 2 were used in the real-time test application with the developed agricultural UAV.

In Approach 1, the best F1 score was 98% in 100 epochs with the YOLOv5s model. In Approach 2, the best F1 score and mAP values were obtained as 98.6% and 98.9% in 150 epochs, with the YOLOv5m model with an improvement of 0.6% in the F1 score. In real-time tests, the AI-based spraying drone system detected and sprayed cherry trees with an accuracy of 66% in Approach 1 and 77% in Approach 2. It was revealed that the use of pesticides could be reduced by 53% and the energy consumption of the spraying system by 47%.

An original data set was created by designing an agricultural drone to detect and spray cherry trees using AI. YOLOv5, YOLOv7 and YOLOv8 models were used to detect and classify cherry trees. The results of the performance metrics of the models are compared. In Approach 2, a method including HE, Gaussian and WT is proposed, and the performance metrics are improved. The effect of the proposed method in a real-time experimental application is thoroughly analyzed.

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.

This research study aims to minimize autonomous flight cost and maximize autonomous flight performance of a slung load carrying rotary wing mini unmanned aerial vehicle (i.e. UAV) by stochastically optimizing autonomous flight control system (AFCS) parameters. For minimizing autonomous flight cost and maximizing autonomous flight performance, a stochastic design approach is benefitted over certain parameters (i.e. gains of longitudinal PID controller of a hierarchical autopilot system) meanwhile lower and upper constraints exist on these design parameters.

A rotary wing mini UAV is produced in drone Laboratory of Iskenderun Technical University. This rotary wing UAV has three blades main rotor, fuselage, landing gear and tail rotor. It is also able to carry slung loads. AFCS variables (i.e. gains of longitudinal PID controller of hierarchical autopilot system) are stochastically optimized to minimize autonomous flight cost capturing rise time, settling time and overshoot during longitudinal flight and to maximize autonomous flight performance. Found outcomes are applied during composing rotary wing mini UAV autonomous flight simulations.

By using stochastic optimization of AFCS for rotary wing mini UAVs carrying slung loads over previously mentioned gains longitudinal PID controller when there are lower and upper constraints on these variables, a high autonomous performance having rotary wing mini UAV is obtained.

Approval of Directorate General of Civil Aviation in Republic of Türkiye is essential for real-time rotary wing mini UAV autonomous flights.

Stochastic optimization of AFCS for rotary wing mini UAVs carrying slung loads is properly valuable for recovering autonomous flight performance cost of any rotary wing mini UAV.

Establishing a novel procedure for improving autonomous flight performance cost of a rotary wing mini UAV carrying slung loads and introducing a new process performing stochastic optimization of AFCS for rotary wing mini UAVs carrying slung loads meanwhile there exists upper and lower bounds on design variables.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

The purpose of this paper is to provide details of recent developments in agricultural robots with an emphasis of those that address labour shortages and environmental issues.

Following an introduction which highlights some of the challenges facing the agricultural industry, this discusses recent robotic agricultural vehicle developments and the enabling technologies. It then provides examples of terrestrial and airborne robots employed in precision agricultural practices. Finally, brief conclusions are drawn.

Traditional, labour-intensive and environmentally harmful agricultural practices are not sustainable in the long term, and if food supply is to meet future demand, radical changes will be required. Exploiting recent advances in artificial intelligence (AI), agricultural equipment manufacturers are developing robotic vehicles in response to labour shortages. Precision agricultural practices will mitigate many of the detrimental environmental impacts and can also reduce the reliance on manpower. Weeding robots which reduce or eliminate the use of herbicides have been commercialised by a growing number of companies and again exploit AI techniques. Drones equipped with imaging device are playing an increasingly important role by characterising agricultural and crop conditions, thereby allowing highly targeted agrochemical application.

This illustrates how the agricultural industry is adopting robotic technology in response to the need to increased productivity while mitigating the problems of shortages of labour and environmental degradation.

The purpose of this paper is to systematically review the functionalities, safety regulations and product applications of herb Stevia rebaudiana extract. This plant material is embedded with multiple functionalities such as antioxidant, antidiabetics, anti-inflammation and antimicrobial. The regulations released from global authorities are covered to ensure the safety premise of stevia. Besides, the product applications of the extract of aerial parts of the herb S. rebaudiana helps us to recognize its value from commercial side.

Relevant literatures are selected and obtained from main scientific databases such as Google Scholar, Web of Science, PubMed and trade magazines published between 2000 and 2023. The keywords and their possible combinations such as sweetening, antioxidant, antidiabetics, anti-inflammation, safety and product development were used to ensure the preciseness and completeness of literature searching. Major data such as sweetness, total phenolic content and dose together with latter critical conclusions from searched publications were appropriately used and discussed. In this review, approximately 150 scientific literatures were meticulously ordered and analyzed. In applications, it is the first time that sentiment analysis was used to obtain a market assessment of the stevia-containing products.

This review paper helps rearrange the scientific affairs of those stevia extract’s functions like sweetening, antioxidant, antidiabetics and inflammation. Sweetness indexes of steviol glycosides were summarized together for comparison while various in vitro and in vivo approaches were reviewed to quantify those functions’ capacities and to depict the related mechanism. The regulation of steviol glycoside compounds such as rebaudioside A was established by global authorities such as US Food and Drug Administration and Joint FAO/World Health Organization Expert Committee to ensure the safety endorsement before commercialization. Then, this study discussed about the market performance of stevia ingredients or products with the self-developed data analytics. This study also investigated the product development progress of stevia-containing food products in the categories of beverage, bakery, dairy and confectionery. Those stevia-containing food consumer goods can be acceptable by certain consumers.

This review paper precisely presents the evidential information about the stevia’s multiple functionalities with mechanisms and global regulation milestones. To the best of the authors’ knowledge, it is then the first time to probe the stevia-containing products’ market performance through data analytics.

This study presents the results of an assessment of the barriers that can hinder the deployment of robotics and automation systems in developing countries through the lens of the Nigerian construction industry.

A scoping literature review was conducted through which barriers to the adoption of robotics and automation systems 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 percentages, frequencies, mean item scores and exploratory factor analysis.

Based on the mean scores, the top five barriers were the fragmented nature of the construction process, resistance by workers and unions, hesitation to adopt innovation, lack of capacity and expertise and lack of support from top-level managers. Through factor analysis, the barriers identified were categorized into four principal clusters namely, industry, human, economic and technical-related barriers.

This study provided a good theoretical and empirical foundation that can be useful to construction industry stakeholders, decision-makers, policymakers and the government in mapping out strategies to promote the incorporation and deployment of automation and robotics into the construction industry to attain the safety benefits they offer.

By identifying and evaluating the challenges that hinder the implementation of robotics and automation systems in the Nigerian construction industry, this study makes a significant contribution to knowledge in an area where limited studies exist.

With the popularity of high-rise buildings, wall inspection and cleaning are becoming more difficult and associated with danger. The best solution is to replace manual work with wall-climbing robots. Therefore, this paper proposes a design method for a rolling-adsorption wall-climbing robot (RWCR) based on vacuum negative pressure adsorption of the crawler. It can improve the operation efficiency while solving the safety problems.

The pulleys and tracks are used to form a dynamic sealing chamber to improve the dynamic adsorption effect and motion flexibility of the RWCR. The mapping relationship between the critical minimum adsorption force required for RWCR downward slip, longitudinal tipping and lateral overturning conditions for tipping and the wall inclination angle is calculated using the ultimate force method. The pressure and gas flow rate distribution of the negative pressure chamber under different slit heights of the negative pressure mechanism is analysed by the fluid dynamics software to derive the minimum negative pressure value that the fan needs to provide.

Simulation and test results show that the load capacity of the RWCR can reach up to 6.2 kg on the smooth glass wall, and the maximum load in the case of lateral movement is 4.2 kg, which verifies the rationality and effectiveness of the design.

This paper presents a new design method of a RWCR for different rough wall surfaces and analyses the ultimate force state and hydrodynamic characteristics.