The Interchangeable Use of Unmanned Aerial Systems

UAS Project (Business for Package Delivery) 

Unmanned Aerial System (UAS) is an emerging technology that promises to revolutionize service delivery in the freight and logistics industry. Several factors contributed to the rapid advancement in technology that culminated in the emergence of UAS as a leading technology in the contemporary freight industry. Kaya et al., (2019) posited that the continued emphasis on speed and improved service delivery by players in the industry significantly contributed to increased preference for UAS ns drone technologies. Other researchers argue that the use of drone technology in the delivery of goods was a predictable development considering the upward trajectory in regard to the use of technology in the industry over the years. Stakeholders in the industry are in consensus that UAS is the right step in increasing efficiency and overcoming challenges such as pollution. Hence, this paper discusses various technologies that are critical in the evolution and continued development of UAS in the freight and logistics industry, the successes of UAS and drone technologies in the industry, risks, and challenges of these technologies and the mitigating factors. 

Operation 

The interchangeable use of Unmanned Aerial Systems (UAS) and Unmanned Aerial Vehicles (UAV) fails to give a clear distinction between the two. UAS are the mechanism involved in facilitating the movement of drones as they transport goods, and it involved all the control systems, personnel, and technologies involved. UAV are the actual tools or drones involved in transporting the goods. The operation of UAV relies on an autonomous system of navigation and target recognition for its controlled (R/C) aircraft. The Ardupilot consists of a camera that transmits real-time video imagery to a computer at the ground station. Safety is a crucial component of the system, and there are several fail-safe measures to avoid accidents and other incidences. The leading providers of UAS services in the United States and Europe are Airdata UAV, 3DR, MBPower, and Juniper; hence their technologies are the most pervasive in UAS operations. These technologies include various layers of operations that work simultaneously to facilitate the effective operation of the UAS. 

Three main sub-systems make up the UAS, the ground system, flight, and payload system. The ground system consists of a computer connected to the UAV from where the controller can upload flight plans, view multiple elements relating to flight, and enable the autopilot. The ground is, therefore, key to the navigation coordinates of the device. The flight system, on the other hand, is the body of the UAV together with installed software such as the autopilot for autonomous control and the physical airframe of the vehicle. The payload is comprised of four main parts, the Ardupilot, a camera system, battery, and transmitters. The Ardupilot provides for autonomous navigation of the UAS while the camera system provides imagery that is then transmitted to the ground station. Transmitters enhance the connection to the ground station to enable proper control and uploading of flight coordinates. The design of modern UAS is such that each component of the payload has contained in independent compartments for easier maintenance (Papageorgiou, 2016). The ground computer is connected to the payload through transmits and receives real-time telemetry data that facilitates control through the uploading of coordinates. 

Flight data for UAS varies depending on the size of the UAV, its payload, length of flight, among other factors. Flight data, just like in manned planes, allows the controller to make the decision that facilitates navigation and landing. Lithium Polymer batteries are the most common in UAV and are capable of providing for up to 30 minutes of flight before recharge or replacement. The ground controller receives an alert on their computer from the Ardupilot once the voltage goes below the threshold. Emergencies such as loss of control by the autopilot may occur, thus the provision for safety control to apply. The Futaba T7C remote control is the most common and allows the controller to land the aircraft from the ground location in a clear path. UAS, just like manned aircraft, have restrictions that operators must adhere to facilitate safety (Hamilton, Bliss and Depperschmidt, 2017). Restriction on harsh weather patterns is necessary to ensure the UAS only flies in appropriate weather to avoid accidents and other inconveniences. Altitude restriction enhances aviation safety by avoiding disruptions of manned planes, and restriction in certain airspace is part of the safety measures. The fail-safe mechanism is the most critical safety measure of UAS. This mechanism works by alerting the ground control about certain disruptions in the control of the aircraft, thus allowing the controller to take appropriate action according to the nature of the problem. Loss of radio connection is a possible risk in the UAS, which is mitigated by the Ardupilot taking over the control of the UAS and landing in an appropriate location. As such, each subsystem of the UAS facilitates navigation and also contributes to the safety of the aircraft considering the severity of certain risks that exist with the UAS system. 

SWOT Analysis 

SWOT analysis of the payload is critical in understanding both the strengths and opportunities that players in the industry can leverage for better efficiency as well as the challenges that are likely to hinder growth. Rapid advancement in technology promises increased efficiency through faster and cheaper drones as well as cargo safety. The ability of UAV to perform several functions allows companies to diversify their operations. As such, they can access multiple ranges of the client, which enables the spread of risks and increased profitability. Increased capabilities of UAS allow the aircraft not only to transport heavy cargo but also safely hand fragile goods. As providers of UAS services continue to innovate and provide systems with improved capabilities, a whole range of cargo can be transported to even the remotest locations. These service providers should, therefore, focus on these strengths to cement their position in the business and project UAS as the preferred option in freight and logistics in the future. As such, the controller has access to data, including the altitude, latitude, location, wind speed, UAV speed and direction, and battery voltage. This information thus becomes key to guiding the ground station controller to ensure proper navigation of the UAS as well as landing. 

Weaknesses in the UAS are a motivator for providers to make adjustments that minimize these downsides and accelerate improvement in the business. The biggest challenge for companies is to acquire costly drones. Drones are a fairly new technology that comes at a cost, in addition to the various support systems that accompany the effective application of the UAS. These costs eventually pass to the customers who have to pay for the extra cost of acquiring the equipment. Continued innovation with better funding will reduce significantly lower these costs in the future. The fragility of the drones is also another concern that providers have to deal with when providing services. Any damage to the UAV can cost millions; hence care is necessary to ensure they do not undergo any damage. As such, the companies employ experts with the skills of controlling the drones from the ground. Ground operations also mean that controllers have to rely on the interface that links data to their stations. Transmission of false or disruptions in communication can be catastrophic in some instances. Normal flights for UAV average 30 minutes at speeds of up to 60 km/h. UAS are only allowed to navigate at low altitude with a maximum of 4000 feet to avoid interference with manned aircrafts. The ardupilot eases the control process on the ground by computing the appropriate data and determining the best path for navigation. 

Despite the weaknesses, several opportunities present, which underlines the relevance of UAS as the future of freight and logistics. UAS are an adaptable technology that can function in almost every business in the United Staes and worldwide. Drones can transport medicines to remote areas and also make deliveries within major cities. Such an opportunity reveals that the use of UAS in freight and logistics is largely unexplored. Another opportunity is that drones can cover vast areas within a short time, unlike most present means of transport. Companies can, therefore, make several deliveries in a day, thus cutting on costs and the number of people required to complete operations. Speed also sets UAS apart from other methods currently in use due to timely deliveries and a lack of susceptibility to delays. Threats to UAS include competition, frequent upgrades, and explicit ground control. Businesses are mainly dependent on other delivery platforms; hence it will take time for people to embrace drone technology fully. UAS also requires frequent upgrades to perform optimally, which can be costly and time-consuming. Explicit ground control also means that some night deliveries are difficult to undertake. However, mitigating these threats is crucial in improving the efficiency of UAS. 

Risk Assessment 

Risk assessment for UAS is critical to the development of systems that are safe, fast, and adaptable to the needs of the industry. The assessment process involves the identification of potential threats, identification of their severity, and evaluation of their impact. Mitigation efforts tend to reduce the severity of these threats or to eliminate them in the entirety (Allouch, Koubaa, Khalgui, & Abbes, 2019). Risk assessment for UAS covers the risks from the moment the UAV is on the ground to its flight path and landing for delivery. The pre-flight risks for UAS are abnormal payload and failure to undertake the correct pre-flight procedures. An abnormal payload presents the risk of poor functionality for the Ardupilot, which results in poor communication with the ground workstation. As such, navigation becomes affected, thus limiting the level of control that workstations can exert. Furthermore, an unprocedural approach to preparation for the UAV to take flight can result in hitches through the flight and when landing. These pre-flight risks are severe and can cause accidents with massive losses and loss of customer trust. 

Procedural failure before takeoff is a significant risk to be considered before takeoff. The ground teams have to ensure that the XBEE PRO 900 XSC software is configured correctly before the vehicle leaves the ground. Its failure to configure means that software does not utilize the graphical interphase to connect workstation; hence operators lack control over the flight path of the drone (Kelly, 2017). Another UAV taking off or landing is likely to collide with the unpaired drone, thus increasing the risk of accidents and losses. Transit risks are the most critical for any UAV and impact on several areas of operation. Ardupilot’s fail-safe system works by transmitting information to the operators about weather conditions and the location of the UAV. Failure of the system can be catastrophic, especially in unfavorable weather conditions, which could cause the device to go down. Failure of the Ardupilot can also inhibit safe landing, thus causing damage to both the device and the cargo. Evaluation of landing risks is also necessary to determine the appropriateness of the environment. Poor application of the UAS by the control center can cause the Ardupilot to lose control of the device. Such instances cause emergencies in landing despite the appropriate functionality of the software. There is also the risk of the drone failing to attain the designated height of forty feet during the flight. The result of such an occurrence can also be severe such as collision with manned aircrafts. 

Mitigating Risks 

Risk mitigation is crucial in avoiding unwanted occurrences either due to errors by the controllers or unforeseen events during operation. Mitigation plans for each of the risks depend on the appropriateness of the procedure that will effectively prevent unforeseen occurrences. For instance, the pre-flight risk of an abnormal payload is mitigated by revising the design of the UAV and identifying the design glows that could cause such a problem. An integration plan is then made to normalize the payload and restore the functionality of the drone. Pre-flights risks are also mitigated by confirming the functionality of the Ardi-fail-system (Sangaiah, Samuel, Li, Abdel-Basset, & Wang, 2018). As such, the ground team can ascertain the condition of the drone before the flight. Proper training of ground staff and managers improves their skills in identifying risks before they mature into problems for the business process. Such training should include failure in the pairing of the mounted antenna with the control room during takeoff and the best controls during harsh weather conditions. 

The Future of Unmanned Aerial System (UAS) in Freight and Logistics 

Predictions for increased use of UAS over the next two decades rely on the current trends in the market. The past year saw the spike in the use of UAS, which as more companies expanded their capacity to accommodate the advanced technology. The ability of the current market to sustain this trend is undoubted due to their efficiency through speed and accuracy. The demand for UAV is an appropriate indicator of their future in the freight and logistics industry. Hanscom & Bedford (2013) provide insights into the future demand for UAV in the next 15 years. They opine that a majority of the UAS purchased will be small or media to cost considerations. These UAS will mainly serve commercial purposes as opposed to military use. The rise is the commercial application will be due to the discovery of niches in the current market. Undoubtedly, this prediction supports Kaya et al. (2019) that players in the freight and logistics industry will continue to encourage the development of UAV due to their speed and efficiency. A surge in the purchase of UAV will likely last to the end of the decade to meet the needs of initial innovators and early adaptors, although the trend is set to stabilize once the initial needs are met. 

More specific to the logistics industry, Jenkins et al. (2017) make forecasts about the use of UAS in specific areas. Regulations by the Federal Aviation Administration require the registration of all UAV weighing between half a pound and 55 pounds. The statistics as of 2017 showed that there were over 100 UAVs used for commercial purposes, numbers that were expected to grow to up to 500,000 in the next five years (Jenkins et al., 2017). Although these numbers do not represent only the UAS used in logistics, the industry makes up a significant portion of the lot. Several contributing factors are responsible for the continued preference of UAS in logistics. UAS are a disruptive technology that will significantly change the way goods are delivered to homes or small businesses in the last mile. Cost is a significant factor in the decision by customers on the most appropriate delivery system. Considering that UAS will reduce the cost of delivery by up to one dollar per item, there will be an increased preference for this technology. Total savings for logistics companies will be between $2 billion to$10 billion annually. Such a forecast point to a future where unmanned aerial systems will dominate crucial aspects of logistics services. 

The potential economic benefits of utilizing UAS for package delivery in urban areas is quantifiable. Narkus-Kramer (2017) forecasted that the economic benefits of UAS for package delivery would reach trillions of dollars between 2025 and 2050. As more UAS takes to the sky to deliver packages in metropolitan areas, the compounded benefits to the economy will grow exponentially from the current applications. These benefits will, however, come at a cost as thousands of UAS crisscross the low skies at any given point. As such, the management of these devices over the low-altitude areas will become a necessity. The current capacity of the FAA does not meet the need for thousands of UAS in the sky. Continued improvement and collaboration with other stakeholders are therefore necessary to attain the capacity needed to manage UAS activities, especially in metropolitan areas, effectively. 

Conclusion 

Unmanned Aerial System (UAS) is certainly a disruptive technology that will shape the future of the logistics industry. This statement is especially true in the last mile disruption, where UAS promises massive cost-saving amounting to billions of dollars and better efficiency in service delivery. Unlike tracks that take hours to deliver packages to businesses, UAS can perform the same tasks in minutes. Continued innovations by leading companies such as Airdata UAV, 3DR, MBPower promise to change the way UAS are utilized commercially. Forecasts on the use of UAS in logistics have that over 500,000 UAS will be operational in metropolitan areas in the US, delivering packages resulting in saving of up to $10 trillion annually by 2050 (Jenkins et al., 2017). There are, however, challenges and risks involved in the use of UAS that industry players have to overcome and mitigate for the aforementioned predictions to materialize. The challenges include high initial costs for the UAS, stiff competition from other delivery platforms, and fragility of the aircrafts currently in use. Risk includes failure in radio transmission during flight, problems with payload, and human error. These risks can be mitigated through proper training, improved design, and problem diagnosis at different levels. Criticism for UAS use in delivery services has also surfaced, with some arguing that they lack privacy. Despite these challenges, UAS in logistics is a developing technology the promises efficiency in service delivery, savings in costs and reduced pollution 

References 

Allouch, A., Koubaa, A., Khalgui, M., & Abbes, T. (2019). Qualitative and quantitative risk analysis and safety assessment of crewless aerial vehicles missions over the internet. IEEE Access ,  7 , 53392-53410. https://arxiv.org/abs/1904.09432 

Hamilton, O., Bliss, T. and Depperschmidt, C. (2017). Integration of Military Unmanned Aerial Systems (UAS) into the US National Airspace System: The relationship between UAS accidents and safety concerns.  International Journal of Aviation, Aeronautics, and Aerospace . doi: 10.15394/ijaaa.2017.1150 

Hanscom, A. F. B., & Bedford, M. A. (2013). Unmanned aircraft system (UAS) service demand 2015–2035, literature review & projections of future usag e. Res. Innov. Technol. Admin., US Dept. Transp., Washington, DC, USA. 

Jenkins, D., Vasigh, B., Oster, C., & Larsen, T. (2017). Forecast of the commercial UAS package delivery market. Embry-Riddle Aeronautical University. 

Kaya, U. C., Dogan, A., & Huber, M. (2019). A Utility-Based Path Planning for Safe UAS Operations with a Task-Level Decision-Making Capability. In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) (pp. 1227-1233). IEEE. 

Kelly, T. A. (2017, April). Risk assessment for application of sensor technologies to overcome the security risks of unmanned systems. In  2017 IEEE International Symposium on Technologies for Homeland Security (HST)  (pp. 1-3). IEEE. 

Narkus-Kramer, M. P. (2017). Future demand and benefits for small unmanned aerial systems (UAS) package delivery. In 17th AIAA Aviation Technology, Integration, and Operations Conference (p. 4103). 

Papageorgiou, E. (2016).  Value Driven Unmanned Air System Design . Lambert Academic Publishing. 

Sangaiah, A. K., Samuel, O. W., Li, X., Abdel-Basset, M., & Wang, H. (2018). Towards an efficient risk assessment in software projects–Fuzzy reinforcement paradigm.  Computers & Electrical Engineering ,  71 , 833-846.