Search

Unmanned Aerial Vehicles (UAVs), commonly known as drones, show great potential in advancing the United Nations (UN) Sustainable Development Goals (SDGs), a collection of 17 worldwide targets outlined by the United Nations (UN) to tackle diverse social, economic, and environmental issues and foster sustainable development by 2030. As per the Federal Aviation Administration (FAA), UAVs can significantly improve areas of sustainability like wildlife and wildfire monitoring, precision agriculture, as well as healthcare. Furthermore, drones with communication capabilities are seen as key elements of non-terrestrial networks, and as enabling technologies for future 6G communication networks. This systematic literature review focuses on the role of UAV-enabled communications to achieve the SDGs. Our study is based on a thorough selection and analysis of scientific articles. Initially, we performed a broad search across three major databases: IEEE Xplore, Web of Science, and Scopus, yielding a set of 10,499 papers. Following a strict selection methodology (Preferred Reporting Items for Systematic Review and Meta-Analysis - PRISMA), we narrowed this set down to 28 key journal articles. Our analysis highlights six global targets that greatly benefit from UAV-enabled aerial communication. In order of impact, these are: “Sustainable Cities and Communities,” where UAVs improve security and disaster management; “Life on Land,” where drones help with wildlife monitoring and reforestation; “Industry, Innovation, and Infrastructure,” where UAVs (Unmanned Aerial Vehicles) aid in infrastructure inspection; “No Hunger,” where drones improve agricultural practices; “‘Good Health and Wellbeing,” where UAVs assist with disease prediction and monitoring; and “Clean water and sanitation,”where drones play a crucial role in efficiently monitoring water quality and distribution. In summary, this paper offers a detailed look at the applications of UAVs in achieving the SDGs through aerial communications. By identifying areas of major impact and spotting gaps and weaknesses in current research, this review article aims to guide future research and policy-making in sustainable drone applications.

The exploitation of unmanned aerial vehicles (UAVs) in enhancing network performance in the context of beyond-fifth-generation (5G) communications has shown a variety of benefits compared to terrestrial counterparts. In addition, they have been largely conceived to play a central role in data dissemination to Internet of Things (IoT) devices. In the proposed work, a novel stochastic geometry unified framework is proposed to study the downlink performance in a UAV-assisted IoT network that integrates both UAV-base stations (UAV-BSs) and terrestrial IoT receiving devices. The framework builds upon the concept of the aerial UAV corridor, which is modeled as a finite line above the IoT network, and the one-dimensional (1D) binomial point process (BPP) is employed for modeling the spatial locations of the UAV-BSs in the aerial corridor. Subsequently, a comprehensive SNR-based performance analysis in terms of coverage probability, average rate, and energy efficiency is conducted under three association strategies, namely, the nth nearest-selection scheme, the random selection scheme, and the joint transmission coordinated multi-point (JT-CoMP) scheme. The numerical results reveal valuable system-level insights and trade-offs and provide a firm foundation for the design of UAV-assisted IoT networks.

Evidence of the association between dietary habits and long-term body weight status is scarce. This study aimed to evaluate changes in Mediterranean-type diet (MTD) adherence in relation to body weight during 20 years of follow-up. Data from n = 1582 participants from the ATTICA cohort study (2002–2022) were used. MTD adherence was assessed via MedDietScore, and body weight status via body mass index (BMI) by 3 different measurements. We found that MTD adherence and changes in this adherence were inversely related to BMI at 20 years and the mean BMI during the 20-year follow-up. In multi-adjusted linear regression models, a 1/55 increase in baseline, 10-year, and 20-year MedDietScore was associated with a decrease of 0.05–0.13 kg/m2 in BMI at 20 years and of 0.08–0.09 kg/m2 in the mean BMI. Being consistently close to the MTD for 20 years was associated with a >90% decreased risk of maintaining overweight/obesity during the 20-year period. Strong, protective, long-lasting effects of the MTD were observed, even in those who deviated from the MTD in the follow-up (41% of the sample). Our results highlight the need to focus on the overall diet quality to minimize the risk of maintaining an excessive body weight during the life-course.

Maritime activities represent a major domain of economic growth with several emerging maritime Internet of Things use cases, such as smart ports, autonomous navigation, and ocean monitoring systems. The major enabler for this exciting ecosystem is the provision of broadband, low-delay, and reliable wireless coverage to the ever-increasing number of vessels, buoys, platforms, sensors, and actuators. Towards this end, the integration of unmanned aerial vehicles (UAVs) in maritime communications introduces an aerial dimension to wireless connectivity going above and beyond current deployments, which are mainly relying on shore-based base stations with limited coverage and satellite links with high latency. Considering the potential of UAV-aided wireless communications, this survey presents the state-of-the-art in UAV-aided maritime communications, which, in general, are based on both conventional optimization and machine-learning-aided approaches. More specifically, relevant UAV-based network architectures are discussed together with the role of their building blocks. Then, physical-layer, resource management, and cloud/edge computing and caching UAV-aided solutions in maritime environments are discussed and grouped based on their performance targets. Moreover, as UAVs are characterized by flexible deployment with high re-positioning capabilities, studies on UAV trajectory optimization for maritime applications are thoroughly discussed. In addition, aiming at shedding light on the current status of real-world deployments, experimental studies on UAV-aided maritime communications are presented and implementation details are given. Finally, several important open issues in the area of UAV-aided maritime communications are given, related to the integration of sixth generation (6G) advancements. These future challenges include physical-layer aspects, non-orthogonal multiple access schemes, radical learning paradigms for swarms of UAVs and unmanned surface and underwater vehicles, as well as UAV-aided edge computing and caching.

In this paper, we consider the ergodicchannel capacity (ECC) of several generalized fading channels for a mobile user that moves inside a coverage area according to the random waypoint (RWP) mobility model. The ECC with RWP mobility provides the average capacity of a mobile receiver taking into account the probability density function (PDF) of the distance between the user and the transmitting antenna, the path loss exponent and the fading channel. It turns out that the ECC in a mobile environment can be written in terms of the corresponding ECC in the static case. Therefore, we use analytical expressions of the ECC of different generalized fading models for the static channel to derive the corresponding analytical expressions for the ECC in the mobile case. Asymptotic expressions, in the high signal-to-noise ratio (SNR) regime, are also provided that quickly converge to the exact ones. Monte Carlo simulation is also used to show the validity of the derived expressions. The analytical exact and asymptotic expressions enable the system designer to quantify the effect of different physical channel and mobility parameters on the attained average capacity of generalized fading channels.

The cooperative aerial and device-to-device (D2D) networks employing non-orthogonal multiple access (NOMA) are expected to play an essential role in next-generation wireless networks. Moreover, machine learning (ML) techniques, such as artificial neural networks (ANN), can significantly enhance network performance and efficiency in fifth-generation (5G) wireless networks and beyond. This paper studies an ANN-based unmanned aerial vehicle (UAV) placement scheme to enhance an integrated UAV-D2D NOMA cooperative network.The proposed placement scheme selection (PSS) method for integrating the UAV into the cooperative network combines supervised and unsupervised ML techniques. Specifically, a supervised classification approach is employed utilizing a two-hidden layered ANN with 63 neurons evenly distributed among the layers. The output class of the ANN is utilized to determine the appropriate unsupervised learning method—either k-means or k-medoids—to be employed. This specific ANN layout has been observed to exhibit an accuracy of 94.12%, the highest accuracy among the ANN models evaluated, making it highly recommended for accurate PSS predictions in urban locations. Furthermore, the proposed cooperative scheme allows pairs of users to be simultaneously served through NOMA from the UAV, which acts as an aerial base station. At the same time, the D2D cooperative transmission for each NOMA pair is activated to improve the overall communication quality. Comparisons with conventional orthogonal multiple access (OMA) and alternative unsupervised machine-learning based-UAV-D2D NOMA cooperative networks show that significant sum rate and spectral efficiency gains can be harvested through the proposed method under varying D2D bandwidth allocations.

This work establishes a robocentric framework around a non-linear Model Predictive Control (NMPC) for autonomous navigation of quadrotors in tunnel-like environments. The proposed framework enables obstacle free navigation capabilities for resource constraint platforms in areas with critical challenges including darkness, textureless surfaces as well as areas with self-similar geometries, without any prior knowledge. The core contribution of the proposed framework stems from the merging of perception dynamics in a model-based optimization approach, aligning the vehicles heading to the tunnels’ open space expressed in the $x$ axis coordinate in the image frame of the most distant area. Moreover, the aerial vehicle is considered as a free-flying object that plans its actions using egocentric onboard sensors. The proposed method can be deployed in both fully illuminated indoor corridors or featureless dark tunnels, leveraging visual processing from either RGB-D or monocular sensors for generating direction commands to keep flying in the proper direction. Multiple experimental field trials demonstrate the effectiveness of the proposed method in challenging environments.

In this paper, important statistical characteristics of the ratio of double generalized-gamma random variables have been analytically evaluated. The derived results have been applied in a wireless powered mobile-to-mobile communication scenario, which operates in the presence of interference. The performance is investigated using the throughput criterion under two different scenarios, namely delay limited and delay tolerant transmissions. Moreover, since the links’ reliability depends on the mobile nodes locations, the $2D$ Poisson point process is employed in order to more realistically model the physical layer behavior. The analytical results provided generalize previously reported ones, while the numerical results presented reveal the impact of various system’s and channel’s parameters, e.g., distance among nodes, interference, the non-linearity of the wireless medium.

In this work, a mathematical framework to evaluate the performance of a finite, three dimensional (3D) unmanned aerial vehicle (UAV) network in the presence of interference is developed. The framework builds upon stochastic geometry tools and specifically the binomial point process (BPP) for the spatial distribution of the UAVs. A UAV base station (UAV-BS) reference receiver is located at the center of a sphere and communicates with the nearest transmitting UAV node, whose distance from the UAV-BS reference receiver is either fixed or random. The reverse link suffers from the presence of a single dominant interferer, whose location is random within the sphere. Closed-form expressions are derived for statistical metrics of the signal-to-interference ratio (SIR) for two scenarios, namely for fixed or random location of the desired transmitting node. Then, the impact of the location of the transmitting node on the coverage probability (CP) is studied while the average error probability and the ergodic capacity have been also analytically investigated. Finally, the theoretical results are numerically evaluated and compared to simulation to reveal some useful insights.

In this paper we study the effect of user mobility on the performance of wireless digital receivers operating in the presence of fading, shadowing, and path loss. Recently, it was shown in (Lopez-Fernandez et al., 2018) that the distribution of the received power of a mobile receiver is given by the incomplete moment of the underlying static fading distribution. In this paper, we consider the random waypoint mobility model and show that, in fact, other performance metrics of the mobile receiver can be expressed in terms of statistical characterizations of the fading distribution in the static case. We consider the moment generating function of the received signal-to-noise ratio (SNR), the average bit error rate and the average channel capacity and present analytical results for these performance metrics in different generalized fading environments. Asymptotic expressions are also derived that converge to the exact performance at high values of the SNR. Numerical results are provided to quantify the effects of network dimension, path loss coefficient and fading model parameters on the performance metrics of the mobile receiver.

Multi-Antenna communication techniques are an efficient and relatively simple approach for the performance improvement of wireless communication systems. However, the direct application of multi-antenna techniques to an aerial communication system is not always feasible due to the constraints induced by the aerial platforms. Reconfigurable intelligent antenna technologies could provide an efficient solution to these problems and thus they are considered as ideal candidates for adaption in the aerial communication platforms that will be used in the 5G and beyond communication networks. In this paper, a joint Tx-Rx beamforming with beam selection and combining technique is proposed for improving the performance of an aerial communication system supported by electronically steerable antenna arrays. The main idea of the proposed scheme is to select, using an SNR maximization criterion, a pair of beam patterns between each RF chain of the ground station and the aerial platform, and combine the received SNRs under the maximal ratio principle. Initially, an analytical stochastic framework has been developed that is based on a Markov chain model, which is used to investigate the statistics of the received SNR. Then, an implementation of the novel beamforming and pattern adaptation scheme is presented, with the use of Electronically Steerable Parasitic Array Radiators (ESPAR), properly designed for Ground Station to UAV links. In addition, a realistic simulator is also developed with proper channel model selection, by the aid of which, the performance of the proposed scheme has been evaluated in conjunction with the extracted analytical results.

Motion Shield is an automatic crash notification system that uses a mobile phone to generate automatic alerts related to the safety of a user when the user is boarding a means of transportation. The objective of Motion Shield is to improve road safety by considering a moving vehicle’s risk, estimating the probability of an emergency, and assessing the likelihood of an accident. The system, using multiple sources of external information, the mobile phone sensors’ readings, geolocated information, weather data, and historical evidence of traffic accidents, processes a plethora of parameters in order to predict the onset of an accident and act preventively. All the collected data are forwarded into a decision support system which dynamically calculates the mobility risk and driving behavior aspects in order to proactively send personalized notifications and alerts to the user and a public safety answering point (PSAP) (112).

Satellite communication systems need to be integrated with emerging cooperative relaying techniques to provide seamless connectivity and high-speed broadband access for mobile users in future wireless networks. In this paper, we study a multi-antenna multiuser hybrid satellite-terrestrial relay network (HSTRN) employing opportunistic user scheduling with outdated channel state information (CSI) and amplify-and-forward relaying with co-channel interference (CCI). By adopting Shadowed-Rician fading for satellite links and Nakagami-m fading for terrestrial links, we derive novel and accurate expressions for outage probability and ergodic capacity of the proposed HSTRN, and further examine its achievable diversity order. More importantly, we conduct the performance analysis by taking both uncorrelated and correlated Shadowed-Rician fading channels into account and show that the antenna correlation at the satellite does not affect the overall system diversity order. Our derived analytical expressions provide efficient tools to characterize the impact of CCI, outdated CSI, and antenna correlation on the system performance of HSTRN with an arbitrary number of satellite antennas, number of interferers, number of users, and integer values of the per-hop fading severity parameters. Our results provide useful guidelines in the design of futuristic HSTRNs for satellite mobile communications.

Vitamin C, a water-soluble compound, is a natural antioxidant in many plant-based products, possessing important nutritional benefits for human health. During fruit and vegetable processing, this bioactive compound is prone to various modes of degradation, with temperature and oxygen being recognised as the main factors responsible for this nutritional loss. Consequently, Vitamin C is frequently used as an index of the overall quality deterioration of such products during processing and post-processing storage and handling. Traditional preservation methods, such as thermal processing, drying and freezing, are often linked to a substantial Vitamin C loss. As an alternative, novel techniques or a combination of various preservation steps (“hurdles”) have been extensively investigated in the recent literature aiming at maximising Vitamin C retention throughout the whole product lifecycle, from farm to fork. In such an integrated approach, it is important to separately study the effect of each preservation step and mathematically describe the impact of the prevailing factors on Vitamin C stability, so as to be able to optimise the processing/storage phase. In this context, alternative mathematical approaches have been applied, including more sophisticated ones that incorporate parameter uncertainties, with the ultimate goal of providing more realistic predictions.

The objective of the study was the kinetic modelling of the shelf-life of osmotically pre-treated fish during refrigerated and super-chilled storage. Fresh gilthead seabream (Sparus aurata) fillets were treated for 0–360 min at 15 °C in osmotic solutions 50:5 high dextrose equivalent maltodextrin:NaCl/100 g (HDM), 40:10:5 HDM:trehalose:NaCl/100 g (HDM + treh) and 40:10:5 HDM:glucosamine:NaCl/100 g (HDM + gluc). Water loss, solid gain, salt content and water activity were monitored throughout treatment. Slices untreated and osmotically pre-treated for 45 min were aerobically packed and stored isothermally at 15, 10, 5, 2.5, 0, −1 and −3 °C. Quality assessment was based on microbial growth (total viable count, Pseudomonas spp., Brochothrix thermosphacta, Enterobacteriaceae spp., H2S-producing bacteria, lactic acid bacteria, yeasts and moulds), total volatile nitrogen (TVB-N), lipid oxidation (TBARs) and sensory scoring. Quality indices were kinetically modelled and temperature dependence of quality loss rates was modelled by Ratkowsky equation. Osmotic pre-treatment led to significant shelf-life extension of fillets, in terms of microbial growth, chemical changes and organoleptic deterioration. The pre-treatment with the alternative solutes led to depression of the freezing point (−1.8, −2.6, −3.2 and −3.5 °C for the untreated samples and the osmotically pre-treated with HDM, HDM + treh and HDM + gluc, respectively). TVB-N values were higher in untreated samples, followed by osmotically treated fillets, mainly at higher storage temperatures (i.e. 10 and 15 °C). Based on the mathematical models for sensory evaluation scoring, the shelf-life was 12, 19, 22 and 22 days at 0 °C for untreated and osmotically pre-treated with HDM, HDM + treh and HDM + gluc fish slices, respectively, while the respective values at −3 °C were 21, 35, 38 and 38 days. The alternative solutes had no significant effect on the quality and shelf-life of pre-treated fish fillet during storage at refrigerated conditions.

In the above article [1], the funding authorities text required a reformatting. The updated text is as follows:

The objective of this study was the investigation of the effect of variable conditions on quality parameters and the shelf life of fish during frozen storage. Three different fish products were tested, i.e., gilthead sea bream (Sparus aurata) fillets, sea bass (Dicentrarchus labrax) fillets, and yellowfin tuna (Thunnus albacares) slices stored in the range of −5 to −15 °C. The kinetic modeling of different shelf-life indices was conducted. Sensory scoring of frozen fish showed high correlation with color (L-value) and total volatile basic nitrogen (TVBN). The temperature dependence of the rates of quality degradation was expressed via the activation energy values, calculated via the Arrhenius equation, and ranged, for the tested quality indices, between 49 and 84 kJ/mol. The estimated kinetic parameters were validated at dynamic conditions and their applicability in real conditions was established, allowing for their practical application as tools for cold chain management.

Osmodehydrofreezing (ODF), a combined preservation process where osmotic dehydration is applied prior to freezing, achieves several advantages, especially in plant tissues, sensitive to freezing. OD pre-treatment can lead to the selective impregnation of solutes with special characteristics that reduce the freezing time and improve the quality and stability of frozen foods. ODF research has extensively focused on the effect of the osmotic process conditions (e.g., temperature, duration/composition/concentration of the hypertonic solution) on the properties of the osmodehydrofrozen tissue. A number of complimentary treatments (e.g., vacuum/pulsed vacuum, pulsed electric fields, high pressure, ultrasound) that accelerate mass transfer phenomena have been also investigated. Less research has been reported with regards the benefits of ODF during the subsequent storage of products, in comparison with their conventionally frozen counterparts. It is important to critically review, via a holistic approach, all parameters involved during the first (osmotic dehydration), second (freezing process), and third stage (storage at subfreezing temperatures) when assessing the advantages of the ODF integrated process. Mathematical modeling of the improved food quality and stability of ODF products during storage in the cold chain, as a function of the main process variables, is presented as a quantitative tool for optimal ODF process design.

The objective of this workwas to investigate the potential use of pulsed electric field (PEF) in combination with osmotic dehydration (OD) as a pre-freezing step and to evaluate the effect on quality characteristics and shelf life of frozen kiwifruit. Peeled kiwifruit was subjected to PEF (1.8 kV/cm), sliced and treated in OD-solution [containing glycerol, maltodextrin, trehalose, ascorbic acid, calcium chloride, citric acid, sodium chloride; 1/5 (wfruit/wsolution)] for 30 and 60 min at 35 °C. Combined, PEF only and OD only treated samples as well as nontreated and blanched (80 °C, 60 s) samples were frozen and stored at constant (-5, -10, -15, -25 °C) and dynamic temperature conditions (-18 °C-3 d, -8 °C-2.5 d, -15 °C-3 d). Quality of frozen samples was evaluated by means of drip loss, colour, texture, vitamin C and sensory evaluation (1-9 scale); and shelf life (SL) was calculated. Nontreated and blanched samples presented high drip loss and tissue softening (instrumentally measured as Fmax decrease). The tissue integrity was well retained in all osmotically pretreated samples. PEF pretreatment caused increase of fruit whiteness (increase of L value) and yellowness (a and/or b value increase); SL calculation was based on colour change. All OD samples had high vitamin content (24.6 mg/100 g fresh material compared to 138-154 mg/100 g osmodehydrated material); PEF led to 93% (of the initial) vitamin retention; blanched samples showed the lowest retention (86.9% of the initial) (criteria for SL calculation). OD and combined PEF-OD treatment increased the shelf life of frozen kiwifruit (up to 3 times; based on sensorial criteria). The developed kinetic models for colour change, vitamin loss, and sensory quality deterioration were validated at dynamic temperature conditions. PEF pretreated OD (at significantly shorter time, 30 min compared to 60 min) kiwifruits retained optimum quality and sensory characteristics. PEF and OD could be used as a preprocessing step of good quality, longer shelf life kiwi sliced frozen products.

In this paper a MMIC QPSK modulator is described. The bit rate of the baseband signal is 155 Mbits/sec, while the frequency of the carrier is fLO=10 GHz . The modulation is performed directly at the RF band and therefore an IF stage is not necessary. The design contains all the necessary sub-circuits except for the demultiplexer and the low-pass filters, which are used so that the bandwidth of the binary waves can be reduced. The mixers that are contained in the circuit are not the typical Gilbert cells and as a result they occupy a much smaller area (half). The circuit needs no external LO coupler and no RF chocks. The F-20 process of GEC Marconi was used for designing the modulator. The occupied area is approximately 12 mm2 . Section 1 presents fundamentals on Quadriphase Shift Keying (QPSK), while in Section 2 the characteristics of the F-20 process are described. In the following Sections the sub-circuits, the complete circuit, and its simulated results are presented.

This paper studies the performance of switch and stay combining (SSC) diversity receivers operating over correlated Ricean fading satellite channels. Using an infinite series representation for the bivariate Ricean probability density function (PDF), the PDF of the SSC output signal-to-noise ratio (SNR) is derived. Capitalizing on this PDF, analytical expressions for the corresponding cumulative distribution function (CDF), the moments of the output SNR, the moments generating function (MGF), and the average channel capacity (CC) are derived. Furthermore, by considering several families of modulated signals, analytical expressions for the average symbol error probability (ASEP) for the diversity receivers under consideration are obtained. The theoretical analysis is accompanied by representative performance evaluation results, including average output SNR (ASNR), amount of fading (AoF), outage probability (Pout), average bit error probability (ABEP), and average CC, which have been obtained by numerical techniques. The validity of some of these performance evaluation results has been verified by comparing them with previously known results obtained for uncorrelated Ricean fading channels.

Undergraduate students participating in the UCLA Undergraduate Research Consortium for Functional Genomics (URCFG) have conducted a two-phased screen using RNA interference (RNAi) in combination with fluorescent reporter proteins to identify genes important for hematopoiesis in Drosophila. This screen disrupted the function of approximately 3500 genes and identified 137 candidate genes for which loss of function leads to observable changes in the hematopoietic development. Targeting RNAi to maturing, progenitor, and regulatory cell types identified key subsets that either limit or promote blood cell maturation. Bioinformatic analysis reveals gene enrichment in several previously uncharacterized areas, including RNA processing and export and vesicular trafficking. Lastly, the participation of students in this course-based undergraduate research experience (CURE) correlated with increased learning gains across several areas, as well as increased STEM retention, indicating that authentic, student-driven research in the form of a CURE represents an impactful and enriching pedagogical approach.

Unmanned Aerial Vehicles (UAVs), commonly known as drones, show great potential in advancing the United Nations (UN) Sustainable Development Goals (SDGs), a collection of 17 worldwide targets outlined by the United Nations (UN) to tackle diverse social, economic, and environmental issues and foster sustainable development by 2030. As per the Federal Aviation Administration (FAA), UAVs can significantly improve areas of sustainability like wildlife and wildfire monitoring, precision agriculture, as well as healthcare. Furthermore, drones with communication capabilities are seen as key elements of non-terrestrial networks, and as enabling technologies for future 6G communication networks. This systematic literature review focuses on the role of UAV-enabled communications to achieve the SDGs. Our study is based on a thorough selection and analysis of scientific articles. Initially, we performed a broad search across three major databases: IEEE Xplore, Web of Science, and Scopus, yielding a set of 10,499 papers. Following a strict selection methodology (Preferred Reporting Items for Systematic Review and Meta-Analysis - PRISMA), we narrowed this set down to 28 key journal articles. Our analysis highlights six global targets that greatly benefit from UAV-enabled aerial communication. In order of impact, these are: "Sustainable Cities and Communities," where UAVs improve security and disaster management; "Life on Land," where drones help with wildlife monitoring and reforestation; "Industry, Innovation, and Infrastructure," where UAVs (Unmanned Aerial Vehicles) aid in infrastructure inspection; "No Hunger," where drones improve agricultural practices; "Good Health and Wellbeing," where UAVs assist with disease prediction and monitoring; and "Clean water and sanitation," where drones play a crucial role in efficiently monitoring water quality and distribution. In summary, this paper offers a detailed look at the applications of UAVs in achieving the SDGs through aerial communications. By identifying areas of major impact and spotting gaps and weaknesses in current research, this review article aims to guide future research and policy-making in sustainable drone applications. [ABSTRACT FROM AUTHOR]