Mobile Network Performance and Technical Feasibility of LTE-Powered Unmanned Aerial Vehicle

Zulkifley, Muhammad Aidiel; Behjati, Mehran; Nordin, Rosdiadee; Zakaria, Mohamad Shanudin

doi:10.3390/s21082848

Cited by 24 publications

(12 citation statements)

References 30 publications

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“…Apart from expertise, infrastructure and regulations [ 14 , 15 ], one of the main barriers to surmount is the question of cost-effectiveness of drone usage. Thus far, there is only one study that attempted to answer the question of cost-effectiveness of drone for medical products transportation, the finding of which showed that motorcycles were more cost-effective than short-range (< 65 km) drones [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Drone versus ambulance for blood products transportation: an economic evaluation study

Zailani

Sabudin

Rahana

et al. 2021

BMC Health Serv Res

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Background Medical transportation is an essential step in health care services, and includes ground, air and water transportation. Among the important uses of medical transportation is the delivery of blood products in the event of a clinical emergency. Drone technology is the latest technological advancement that may revolutionize medical transportation globally. Nonetheless, its economic evaluation is scant and insufficient, whilst its cost-effectiveness remains controversial. The aim of this study was to compare the cost-effectiveness of drone transportation versus the ambulance. Methods The setting of the study was within a developing nation. An economic evaluation study of drone versus ambulance for emergency blood products transportation between the Sabah Women and Children Hospital (SWACH) and the Queen Elizabeth II Hospital (QEH2) on Borneo Island was conducted using the Cost-Effectiveness Analysis (CEA) technique. The total cost of each mode of transportation was calculated using the Activity Based Costing (ABC) method. Travel time was used as a denominator to estimate the Incremental Cost Effectiveness Ratio (ICER). Results For one clinical emergency in SWACH, a round trip of blood products transportation from SWACH to QEH2 costs RM1,266.02 (USD307.09) when using the ambulance, while the drone costs RM1,313.28 (USD319.36). The travel time for the drone was much shorter (18 min) compared to the ambulance (34 min). The Cost-Effectiveness Ratio (CER) of ambulance transportation was RM37.23 (USD9.05) per minute whilst the CER of drone transportation was RM72.96 (USD17.74) per minute. The ICER of drone versus ambulance was − 2.95, implying an increase of RM2.95 in cost for every minute saved using a drone instead of an ambulance. Conclusion Although drone transportation of blood products costs more per minute compared to the ambulance, the significantly shorter transport time of the drone offset its cost. Thus, we believe there is good economic potential for drone usage for blood products transportation in developing nations particularly if the drone price decreases and its operational lifespan increases. Our limitation of a non-clinical denominator used in this study leads to the recommendation for use of clinical outcomes in future studies.

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Section: Introductionmentioning

confidence: 99%

Drone versus ambulance for blood products transportation: an economic evaluation study

Zailani

Sabudin

Rahana

et al. 2021

BMC Health Serv Res

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“…Drones have recently been used as flying cellular base stations (BSs) to deliver reliable and energy-efficient IoT communications [77], [78]. Such deployment of BSs would increase the probability of LOS communication and mitigate destructive effects such as shadowing and blockage, thereby increasing the reliability of communication links [79].…”

Section: G Unmanned Aerial Vehicles (Uavs)mentioning

confidence: 99%

Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

et al. 2022

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The Internet of Things (IoT) has rapidly expanded for a wide range of applications towards a smart future world by connecting everything. As a result, new challenges emerge in meeting the requirements of IoT applications while retaining optimal performance. These challenges may include power consumption, quality of service, localization, security, and accurate modeling and characterization of wireless channel propagation. Among these challenges, the latter is critical to establishing point-to-point wireless communication between the sensors. Channel modeling also varies depending on the features of the surrounding area, which have a direct impact on the propagation of wireless signals. This presents a difficult task for network planners to efficiently design and deploy IoT applications without understanding the appropriate channel model to analyze coverage and predict optimal deployment configurations. As a result, this challenge has attracted considerable interest in academic and industrial communities in recent years. Therefore, this review presents an overview of current breakthroughs in wireless IoT technologies. The challenges in such applications are then briefly reviewed, focusing on wireless channel propagation modeling and characterization. Finally, the study gives a generalized form of commonly used channel models and a summary of recent channel modeling developments for wireless IoT technology. The outcome of this review is expected to provide a new understanding of the propagation behavior of present and future wireless IoT technologies, allowing network engineers to undertake correct planning and deployment in any environment. Additionally, the study may serve as a guideline for future channel modeling and characterization studies.

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“…For instance, ref. [ 24 ] reviewed the recently developed state-of-the-art air-to-ground channel models for different wireless communication technologies, including cellular-connected UAVs. Meanwhile, ref.…”

Section: Related Workmentioning

confidence: 99%

Reliable Aerial Mobile Communications with RSRP & RSRQ Prediction Models for the Internet of Drones: A Machine Learning Approach

Behjati

Zulkifley

Alobaidy

et al. 2022

Sensors

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The unmanned aerial vehicle (UAV) industry is moving toward beyond visual line of sight (BVLOS) operations to unlock future internet of drones applications, including unmanned environmental monitoring and long-range delivery services. A reliable and ubiquitous mobile communication link plays a vital role in ensuring flight safety. Cellular networks are considered one of the main enablers of BVLOS operations. However, the existing cellular networks are designed and optimized for terrestrial use cases. To investigate the reliability of provided aerial coverage by the terrestrial cellular base stations (BSs), this article proposes six machine learning-based models to predict reference signal received power (RSRP) and reference signal received quality (RSRQ) based on the multiple linear regression, polynomial, and logarithmic methods. In this regard, first, a UAV-to-BS measurement campaign was conducted in a 4G LTE network within a suburban environment. Then, the aerial coverage was statistically analyzed and the prediction methods were developed as a function of distance and elevation angle. The results reveal the capability of terrestrial BSs in providing aerial coverage under some circumstances, which mainly depends on the distance between the UAV and BS and flight height. The performance evaluation shows that the proposed RSRP and RSRQ models achieved RMSE of 4.37 dBm and 2.71 dB for testing samples, respectively.

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Mobile Network Performance and Technical Feasibility of LTE-Powered Unmanned Aerial Vehicle

Cited by 24 publications

References 30 publications

Drone versus ambulance for blood products transportation: an economic evaluation study

Drone versus ambulance for blood products transportation: an economic evaluation study

Wireless Transmissions, Propagation and Channel Modelling for IoT Technologies: Applications and Challenges

Reliable Aerial Mobile Communications with RSRP & RSRQ Prediction Models for the Internet of Drones: A Machine Learning Approach

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