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The purpose of this paper is to inspect whether the people in a public place maintain social distancing. It also checks whether every individual is wearing face mask. If both are not done, the drone sends alarm signal to nearby police station and also give alarm to the public. In addition, it also carries masks and drop them to the needed people. Nearby, traffic police will also be identified and deliver water packet and mask to them if needed.

The proposed system uses an automated drone which is used to perform the inspection process. First, the drone is being constructed by considering the parameters such as components selection, payload calculation and then assembling the drone components and connecting the drone with the mission planner software for calibrating the drone for its stability. The trained yolov3 algorithm with the custom data set is being embedded in the drone’s camera. The drone camera runs the yolov3 algorithm and detects the social distance is maintained or not and whether the people in public is wearing masks. This process is carried out by the drone automatically.

The proposed system delivers masks to people who are not wearing masks and tells importance of masks and social distancing. Thus, this proposed system would work in an efficient manner after the lockdown period ends and helps in easy social distance inspection in an automatic manner. The algorithm can be embedded in public cameras and then details can be fetched to the camera unit same as the drone unit which receives details from the drone location details and store it in database. Thus, the proposed system favours the society by saving time and helps in lowering the spread of corona virus.

It can be implemented practically after lockdown to inspect people in public gatherings, shopping malls, etc.

Automated inspection reduces manpower to inspect the public and also can be used in any place.

This is the original project done with the help of under graduate students of third year B.E. CSE. The system was tested and validated for accuracy with real data.

The purpose of this paper is to demonstrate the development of an aircraft-type autonomous portable drone suitable for surveillance and disaster management. The drone is capable of flying at a maximum speed of 76 km/h. This portable drone comprises five distinct parts those are easily installable within several minutes and can be fit in a small portable kit. The drone consists of a ballistic recovery system, allowing the drone landing vertically. The integrated high-definition camera sends real-time video stream of desired area to the ground control station. In addition, the drone is capable of carrying ~1.8 kg of payload.

In order to design and develop the portable drone, the authors sub-divided the research activities in six fundamental steps: survey of the current drone technologies, design the system architecture of the drone, simulation and modeling of various modules of the drone, development of various modules of the drone and their performance analysis, integration of various modules of the drone, and real-life performance analysis and finalization.

Experimental results: the cruise speed of the drone was in the range between 45 and 62 km/h. The drone was capable of landing vertically using the ballistic recovery system attached with it. On the contrary, the drone can transmit real-time video to the ground control station and, thus, suitable for surveillance. The audio system of the drone can be used for announcement of emergency messages. The drone can carry 1.8 kg of payload and can be used during disaster management. The drone parts are installed within 10 min and fit in a small carrying box.

The autonomous aircraft-type portable drone has a wide range of applications including surveillance, traffic jam monitoring and disaster management.

The cost of the cost-effective drone is within $700 and creates opportunities for the deployment in the least developed countries.

The autonomous aircraft-type portable drone along with the ballistic recovery system were designed and developed by the authors using their won technology.

Delivery management of perishable products such as blood in a supply chain is a considerable issue such that the last-mile delivery, which refers to deliver goods to the end user as fast as possible takes into account as one of the most important, expensive and, polluting segments in the entire supply chain. Regardless of economic challenges, the last-mile delivery faces social and environmental barriers to continuing operations while complying with environmental and social standards, therefore incorporating sustainability into last-mile logistic strategy is no longer an option but rather a necessity. Accordingly, the purpose of this paper is to consider a last-mile delivery in a blood supply chain in terms of using appropriate technologies such as drones to assess sustainability.

The authors discuss the impact of drone technology on last-mile delivery and its importance in achieving sustainability. They focus on the effect of using drones on CO₂ emission, costs and social benefits by proposing a multi-objective mathematical model to assess sustainability in the last-mile delivery. A preemptive fuzzy goal programming approach to solve the model and measure the achievement degree of sustainability is conducted by using a numerical example to show the capability and usefulness of the suggested model, solution approach and, impact of drone technology in achieving all three aspects of sustainability.

The findings illustrate the achievement degree of sustainability in the delivery of blood based on locating distribution centers and allocating drones. Moreover, a comparison between drones and conventional vehicles is carried out to show the preference of using drones in reaching sustainability. A sensitivity analysis on aspects of sustainability and specifications of drone technology is conducted for validating the obtained results and distinguishing the most dominant aspect and parameters in enhancing the achievement degree of sustainability.

To the best of the authors’ knowledge, no research has considered the assessment of sustainability in the last-mile delivery of blood supply chain with a focus on drone technology.

The word “drone” is the common term for an unmanned aerial vehicle – a robot that combines flight with sensors (usually cameras) to allow for unprecedented freedom in observing and interacting with the world.

This column will explore the technology that makes modern drones possible, what makes drones useful and the role of libraries in making drones accessible to their patrons, now and in the future.

Many of these applications are equally appealing to hobbyists and professionals. For some small-scale gardeners, drones can be used to scare away pests, such as deer, or take aerial photographs that provide a new perspective of their garden.

For the agriculture industry, drones already account for $864.4 million in spending per year and are expected to grow to account for over $4 billion by 2022, as they are used not only to monitor and plan crops but also to plant seeds and provide accurate pesticide control (Wood, 2016).

This proposed drone is used for surveillance purpose like medical, agriculture and military in the commercial point of view with less cost and size.

During emergency calls out the technology enabled modes to have quick and timely response for the mankind. As human society continues to spend months together locked inside their homes, it leads to the entire change in the human lifestyle. This also demands the society and the government to get adopt with the technological concepts such as drones to handle this pandemic scenario in a more scientific and safe mode. The major constraints in the utility segment is the cost and performance factor of the drones. This paper aims to design a drone flight management system, which can be used to operate single or multiple drone systems in a wireless mode. The major focus of this work is to minimize the cost of drone flying systems so that it can be accessible to a more massive crowd. The technological design behind the drone has been discussed in detail with mathematical equations. Also the control aspect has been presented in this work. For comparative analysis three drone have been designed and their performance have been compared.

The multi drone is designed , modelling is done and implemented in simulation and hardware. Its having less weight and cost compared to existing drone models.

75% original, 25% of the basic clarifications are taken from existing works.

In recent times, due to rapid urbanization and the expansion of the E-commerce industry, drone delivery has become a point of interest for many researchers and industry practitioners. Several factors are directly or indirectly responsible for adopting drone delivery, such as customer expectations, delivery urgency and flexibility to name a few. As the traditional mode of delivery has some potential drawbacks to deliver medical supplies in both rural and urban settings, unmanned aerial vehicles can be considered as an alternative to overcome the difficulties. For this reason, drones are incorporated in the healthcare supply chain to transport lifesaving essential medicine or blood within a very short time. However, since there are numerous types of drones with varying characteristics such as flight distance, payload-carrying capacity, battery power, etc., selecting an optimal drone for a particular scenario becomes a major challenge for the decision-makers. To fill this void, a decision support model has been developed to select an optimal drone for two specific scenarios related to medical supplies delivery.

The authors proposed a methodology that incorporates graph theory and matrix approach (GTMA) to select an optimal drone for two specific scenarios related to medical supplies delivery at (1) urban areas and (2) rural/remote areas based on a set of criteria and sub-criteria critical for successful drone implementation.

The findings of this study indicate that drones equipped with payload handling capacity and package handling flexibility get more preference in urban region scenarios. In contrast, drones with longer flight distances are prioritized most often for disaster case scenarios where the road communication system is either destroyed or inaccessible.

The methodology formulated in this paper has implications in both academic and industrial settings. This study addresses critical gaps in the existing literature by formulating a mathematical model to find the most suitable drone for a specific scenario based on its criteria and sub-criteria rather than considering a fleet of drones is always at one's disposal.

This research will serve as a guideline for the practitioners to select the optimal drone in different scenarios related to medical supplies delivery.

The proposed methodology incorporates GTMA to assist decision-makers in order to appropriately choose a particular drone based on its characteristics crucial for that scenario.

This research will serve as a guideline for the practitioners to select the optimal drone in different scenarios related to medical supplies delivery.

After completion of the case study, the students will be able to discuss topics such as new venture creation and opportunity sensing, knowledge sharing and employee bonding and the use of social networks in business growth.

This case study focuses on the entrepreneurial journey of Mr Nikhil Methiya, the owner of Dronelab Technology Private Limited, which provides surveying, inspection, agriculture, surveillance and research and development services using drone technologies. This case highlights how Methiya used his minimal resources to grew his business, diversified his activities and developed a sound company profile and work culture to provide the best services to clients. This case also discusses the role of social networks in business growth and expansion, the use of effectuation theory in forming new businesses and the importance of conducting a SWOT analysis to understand a firm’s internal and external environments. Furthermore, this case touches upon the challenges and opportunities of the drone industry in India. It leaves readers in a dilemma should Methiya plan to expand his business to Europe and Africa in the upcoming years. This case study is suitable for postgraduate management students specializing in entrepreneurship and can serve as a valuable resource for the Venture Creation Program’s start-up strategy and execution. The case study’s pedagogy involves discussion-based learning.

This case study can be used in management for an entrepreneurship specialty course. It is ideal for postgraduate students and has a moderate level of difficulty.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.

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.