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Theadvanced air mobility (AAM) is defined by National Aeronautics and Space Administration (NASA) as safe, accessible, automated and affordable air transportation system for passengers and cargo, capable of serving previously hard-to-reach urban and rural sites. The purpose of this paper is to focus on explaining potential solutions, under study by the authors, which could support beyond visual line of sight (BVLOS) operations for goods delivery in a safe way.

According to recent NASA-commissioned market studies, by 2030, there will be as many as 500 million flights a year for package delivery services and 750 million flights a year for passengers’ transportation (AAM). A significant number of these aircrafts will be unmanned aerial vehicles, meaning that they are self-flying or autonomous, of which the smallest ones are quadcopters: they are relatively inexpensive and are capable to perform various tasks, such as aerial observation, crop monitoring and treatment, search and rescue, power line monitoring and goods delivery. On the other hand, there are still many difficulties in introducing them into medium- and low-risk BVLOS routine operations for goods delivery: unfortunately, there are no regulations and technologies yet that enable these operations.

This conceptual paper outlines the studies about possible solutions, identified by authors, which could support BVLOS operations in a medium- and low-risk environment; in particular, the following aspects have been analysed: regulations, integrating control systems for drones, sensors (on board obstacle detection and avoidance), emergency management (emergency on ground system to identify safe landing areas), concepts of droneway (or flight corridors) and drones recovery hub.

The purpose of this paper is to provide a conceptual description of the possible solutions, under study by the authors, which could contribute enabling the BVLOS operations in a medium- and low-risk environment. The paper aims describing the state of the art, terms of regulations, classifications and limitations and describing possible conceptual solutions that could guarantee safety in introducing unmanned aircraft system operations inside urban areas.

A distinctive feature of tilt-rotor UAVs is that they can be fully actuated, whereas in fixed-angle rotor UAVs (e.g. common-type quadrotors, octorotors, etc.), the associated dynamic model is characterized by underactuation. Because of the existence of more control inputs, in tilt-rotor UAVs, there is more flexibility in the solution of the associated nonlinear control problem. On the other side, the dynamic model of the tilt-rotor UAVs remains nonlinear and multivariable and this imposes difficulty in the drone's controller design. This paper aims to achieve simultaneously precise tracking of trajectories and minimization of energy dissipation by the UAV's rotors. To this end elaborated control methods have to be developed.

A solution of the nonlinear control problem of tilt-rotor UAVs is attempted using a novel nonlinear optimal control method. This method is characterized by computational simplicity, clear implementation stages and proven global stability properties. At the first stage, approximate linearization is performed on the dynamic model of the tilt-rotor UAV with the use of first-order Taylor series expansion and through the computation of the system's Jacobian matrices. This linearization process is carried out at each sampling instance, around a temporary operating point which is defined by the present value of the tilt-rotor UAV's state vector and by the last sampled value of the control inputs vector. At the second stage, an H-infinity stabilizing controller is designed for the approximately linearized model of the tilt-rotor UAV. To find the feedback gains of the controller, an algebraic Riccati equation is repetitively solved, at each time-step of the control method. Lyapunov stability analysis is used to prove the global stability properties of the control scheme. Moreover, the H-infinity Kalman filter is used as a robust observer so as to enable state estimation-based control. The paper's nonlinear optimal control approach achieves fast and accurate tracking of reference setpoints under moderate variations of the control inputs. Finally, the nonlinear optimal control approach for UAVs with tilting rotors is compared against flatness-based control in successive loops, with the latter method to be also exhibiting satisfactory performance.

So far, nonlinear model predictive control (NMPC) methods have been of questionable performance in treating the nonlinear optimal control problem for tilt-rotor UAVs because NMPC's convergence to optimum depends often on the empirical selection of parameters while also lacking a global stability proof. In the present paper, a novel nonlinear optimal control method is proposed for solving the nonlinear optimal control problem of tilt rotor UAVs. Firstly, by following the assumption of small tilting angles, the state-space model of the UAV is formulated and conditions of differential flatness are given about it. Next, to implement the nonlinear optimal control method, the dynamic model of the tilt-rotor UAV undergoes approximate linearization at each sampling instance around a temporary operating point which is defined by the present value of the system's state vector and by the last sampled value of the control inputs vector. The linearization process is based on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. The modelling error, which is due to the truncation of higher-order terms from the Taylor series, is considered to be a perturbation that is asymptotically compensated by the robustness of the control scheme. For the linearized model of the UAV, an H-infinity stabilizing feedback controller is designed. To select the feedback gains of the H-infinity controller, an algebraic Riccati equation has to be repetitively solved at each time-step of the control method. The stability properties of the control scheme are analysed with the Lyapunov method.

There are no research limitations in the nonlinear optimal control method for tilt-rotor UAVs. The proposed nonlinear optimal control method achieves fast and accurate tracking of setpoints by all state variables of the tilt-rotor UAV under moderate variations of the control inputs. Compared to past approaches for treating the nonlinear optimal (H-infinity) control problem, the paper's approach is applicable also to dynamical systems which have a non-constant control inputs gain matrix. Furthermore, it uses a new Riccati equation to compute the controller's gains and follows a novel Lyapunov analysis to prove global stability for the control loop.

There are no practical implications in the application of the nonlinear optimal control method for tilt-rotor UAVs. On the contrary, the nonlinear optimal control method is applicable to a wider class of dynamical systems than approaches based on the solution of state-dependent Riccati equations (SDRE). The SDRE approaches can be applied only to dynamical systems which can be transformed to the linear parameter varying (LPV) form. Besides, the nonlinear optimal control method performs better than nonlinear optimal control schemes which use approximation of the solution of the Hamilton–Jacobi–Bellman equation by Galerkin series expansions. The stability properties of the Galerkin series expansion-based optimal control approaches are still unproven.

The proposed nonlinear optimal control method is suitable for using in various types of robots, including robotic manipulators and autonomous vehicles. By treating nonlinear control problems for complicated robotic systems, the proposed nonlinear optimal control method can have a positive impact towards economic development. So far the method has been used successfully in (1) industrial robotics: robotic manipulators and networked robotic systems. One can note applications to fully actuated robotic manipulators, redundant manipulators, underactuated manipulators, cranes and load handling systems, time-delayed robotic systems, closed kinematic chain manipulators, flexible-link manipulators and micromanipulators and (2) transportation systems: autonomous vehicles and mobile robots. Besides, one can note applications to two-wheel and unicycle-type vehicles, four-wheel drive vehicles, four-wheel steering vehicles, articulated vehicles, truck and trailer systems, unmanned aerial vehicles, unmanned surface vessels, autonomous underwater vessels and underactuated vessels.

The proposed nonlinear optimal control method is a novel and genuine result and is used for the first time in the dynamic model of tilt-rotor UAVs. The nonlinear optimal control approach exhibits advantages against other control schemes one could have considered for the tilt-rotor UAV dynamics. For instance, (1) compared to the global linearization-based control schemes (such as Lie algebra-based control or flatness-based control), it does not require complicated changes of state variables (diffeomorphisms) and transformation of the system's state-space description. Consequently, it also avoids inverse transformations which may come against singularity problems, (2) compared to NMPC, the proposed nonlinear optimal control method is of proven global stability and the convergence of its iterative search for an optimum does not depend on initialization and controller's parametrization, (3) compared to sliding-mode control and backstepping control the application of the nonlinear optimal control method is not constrained into dynamical systems of a specific state-space form. It is known that unless the controlled system is found in the input–output linearized form, the definition of the associated sliding surfaces is an empirical procedure. Besides, unless the controlled system is found in the backstepping integral (triangular) form, the application of backstepping control is not possible, (4) compared to PID control, the nonlinear optimal control method is of proven global stability and its performance is not dependent on heuristics-based selection of parameters of the controller and (5) compared to multiple-model-based optimal control, the nonlinear optimal control method requires the computation of only one linearization point and the solution of only one Riccati equation.

This paper aims to assess the behavioural intention of construction organisations to use unmanned aerial vehicles (UAVs) in the delivery of construction projects. Using the unified theory of technology adoption and use of technology (UTAUT) model, the study strives to improve project delivery by adopting beneficial digital technologies.

The study adopted a postpositivism philosophical stance through a quantitative research approach using a structured questionnaire administered to construction organisations in South Africa. Primary data gathered was analysed using frequency, percentage, mean item score, Mann–Whitney U-test and confirmatory factor analysis, where the latter sought to deductively confirm the variables within the UTAUT model.

Construction organisations were found to rarely use UAVs in the country and furthermore, most of the participating organisations are unsure about using UAVs for their project delivery. Factors impacting on an organisation’s intention to use UAVs were identified as social influence, performance expectancy, effort expectancy and facilitating conditions. However, factors surrounding resistance to using and perceived risk cannot be overlooked as they also proved to be significant (at p = 0.05) to the behavioural intention of organisations to use UAVs.

Practical guidance for industry practitioners is offered in terms of insight into the key factors that must be considered for the effective utilisation of UAVs and the realisation of concomitant benefits.

This study bridges the knowledge gap in extant literature by exploring the practitioner’s behavioural intention to use UAVs. As an aside, an emergent theoretical backdrop for future works on UAVs is provided (particularly in developing countries where such a study has not been previously explored).

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.

Organisations and industries are often looking for technologies that can accomplish multiple tasks, providing economic benefits and an edge over their competitors. In this context, drones have the potential to change many industries by making operations more efficient, safer and more economic. Therefore, this study investigates the use of drones as the next step in smart/digital warehouse management to determine their socio-economic benefits.

The study identifies various enablers impacting drone applications to improve inventory management, intra-logistics, inspections and surveillance in smart warehouses through a literature review, a test of concordance and the fuzzy Delphi method. Further, the graph theory matrix approach (GTMA) method was applied to ranking the enablers of drone application in smart/digital warehouses. In the subsequent phase, researchers investigated the relation between the drone application's performance and the enablers of drone adoption using logistic regression analysis under the TOE framework.

This study identifies inventory man agement, intra-logistics, inspections and surveillance are three major applications of drones in the smart warehousing. Further, nine enablers are identified for the adoption of drone in warehouse management. The findings suggest that operational effectiveness, compatibility of drone integration and quality/value offered are the most impactful enablers of drone adoption in warehouses. The logistic regression findings are useful for warehouse managers who are planning to adopt drones in a warehouse for efficient operations.

This study identifies the enablers of drone adoption in the smart and digital warehouse through the literature review and fuzzy Delphi. Therefore, some enablers may be overlooked during the identification process. In addition to this, the analysis is based on the opinion of the expert which might be influenced by their field of expertise.

By considering technology-organisation-environment (TOE) framework warehousing companies identify the opportunities and challenges associated with using drones in a smart warehouse and develop strategies to integrate drones into their operations effectively.

This study proposes a TOE-based framework for the adoption of drones in warehouse management to improve the three prominent warehouse functions inventory management, intra-logistics, inspections and surveillance using the mixed-method.

This work aims to develop a web platform for inspecting roof structures for technical assistance supported by drones and artificial intelligence. The tools used were HTML, CSS and JavaScript languages; Firebase software for infrastructure; and Custom Vision for image processing.

This study adopted the design science research approach, and the main stages for the development of the web platform include (1) creation and validation of the roof inspection checklist, (2) validation of the use of Custom Vision as an image recognition tool, and (3) development of the web platform.

The results of automatic recognition showed a percentage of 77.08% accuracy in identifying pathologies in roof images obtained by drones for technical assistance.

This study contributed to developing a drone-integrated roof platform for visual data collection and artificial intelligence for automatic recognition of pathologies, enabling greater efficiency and agility in the collection, processing and analysis of results to guarantee the durability of the building.

Drones have become an important element within hospitality and tourism. The purpose of this study is to identify the corpus of knowledge and create a research agenda that establishes appropriate guidelines for future study of drone application in hospitality and tourism.

This work has been undertaken using a mixed-methods approach that combines quantitative and qualitative research and includes a review of the literature related to the study of drone use in hospitality and tourism.

The mixed-methods review identified gaps in the research, potential areas of study to enhance the scientific literature and potential uses of drones in tourism and hospitality for researchers, consumers and industry professionals.

This study makes an original contribution by establishing an integrated framework, which led to a synthesis of the research corpus and provided a holistic conceptualisation of the relationship between tourism and drones. In addition, the research agenda proposed will help boost and consolidate this emerging field of research.

无人机已经成为接待和旅游中的一个重要元素。本研究的主要目的是确定知识库, 并建立一个研究议程, 为未来无人机在酒店和旅游业的应用研究建立适当的指导方针。

这项工作采用了混合方法, 将定量和定性研究结合起来, 包括对与酒店和旅游业中无人机使用研究有关的文献进行回顾。

混合方法审查确定了研究中的差距、加强科学文献的潜在研究领域, 以及研究人员、消费者和行业专业人士在旅游和酒店业的无人机应用潜力。

这项研究通过建立一个综合框架做出了原创性的贡献, 它综合合成了研究语料库, 并对旅游和无人机之间的关系提供了一个整体的概念化。此外, 提出的研究议程将有助于促进和巩固这一新兴的研究领域。

Los drones se han convertido en un elemento importante dentro de la hostelería y el turismo. El objetivo principal de este estudio es identificar el corpus de conocimiento y crear una agenda de investigación que establezca las directrices adecuadas para el estudio futuro de la aplicación de los drones en la hostelería y el turismo.

Este trabajo se ha realizado utilizando un enfoque de métodos mixtos que combina la investigación cuantitativa y cualitativa e incluye una revisión de la literatura relacionada con el estudio del uso de drones en hostelería y turismo.

La revisión de métodos mixtos identificó lagunas en la investigación, áreas potenciales de estudio para mejorar la literatura científica y potencial de las aplicaciones de los drones en el turismo y la hostelería para investigadores, consumidores y profesionales del sector.

Este estudio aporta una contribución original al establecer un marco integrado, que conduce a una síntesis del corpus de investigación y proporciona una conceptualización holística de la relación entre el turismo y los drones. Además, la agenda de investigación propuesta contribuirá a impulsar y consolidar este campo de investigación emergente.

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 purpose of the paper is to analyse the sequence of forces acting as barriers in the usage of drones in the construction industry using interpretive structural modelling (ISM). The usage of drones in the construction industry is brought out phase-wise with the help of literature and live cases. Barriers to the usage of drones in construction and steps to derive the interaction between them are described in detail.

The extraction of barriers to the usage of drones in construction is done through cases and supported by the literature. The identification of the interaction between the barriers is done through multi-criteria decision models, namely, ISM and Matriced Impacts Croises Multiplication Appliquee a un Classement (MICMAC) and the results are presented in the form of a hierarchical structure. The paper highlights the potential for the usage of drones in every phase of construction across three stages of construction and eight different applications.

The findings on the interaction between barriers show that technical and research and development-related barriers have a higher driving power, ultimately influencing negativity among stakeholders in drone usage for construction. By analysing interrelationships between barriers, management can frame suitable strategies to adopt drone usage in projects. Awareness about the strength of certain barriers can help management take steps to mitigate the same.

By analysing interrelationships between barriers, management can frame suitable strategies to adopt drone usage in projects. A major limitation is a restriction of the study area to the Indian subcontinent. However, the authors believe that the results can be applied across countries where drone technology is at the nascent stage.

Awareness about the strength of certain barriers can help stakeholders take steps to mitigate the same.

The results of this research also give some inputs to the government’s drone policy for wider usage of drones in the construction industry.

To the best of the authors’ knowledge, most studies on drones in construction industry bring out a list various challenges to their adoption. In this study, the authors have gone further to perform a hierarchical sequencing of barriers to drone adoption based on challenges faced in an emerging economy like India.

After completion of the case study, students will be able to evaluate the journey of launching a business in an emerging market context and judge how opportunities and challenges can be navigated to build sustainable enterprises; assess the relevance of individual attributes and process skills that are necessary for entrepreneurial agency to transform social structures through entrepreneurial action; formulate an argument highlighting the role of the entrepreneurial ecosystem in growing a competitive business in an emerging market context; make an informed decision and critique how accelerators and incubators affect the development of ideas and access to finance in South Africa; and propose various strategic options available for technology entrepreneurs, considering the challenges they face in emerging economies.

In April 2023, Queen Ndlovu, CEO and founder of QP Drone Tech, a provider of drone business solutions, was considering options to fulfil her original dream of manufacturing drones in South Africa. She had encountered obstacles to achieving the same in 2019, and had decided to focus on providing commercial drone consulting services. However, her dream had not extinguished, and in 2022, she decided to restart her efforts. She found practical support from The Innovation Hub, an incubator that was supporting her business, which enabled her to enhance the prototype of her drone. She then had to think about how she would manufacture drones locally by ensuring she had access to production infrastructure, funding, partners and customers. Would she be able to gain a competitive advantage that would differentiate her from competitors? Or should she reconsider whether she should be manufacturing in the first place, as there are risks and benefits for smaller businesses in this regard.

This case is intended for discussion in postgraduate diploma in business and Master of Business Administration courses.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.