Optimal Altitude Research Articles

On-demand UAV base station deployment for wireless service of crowded tourism areas

With the support of wireless network, tourists in tourism areas could enjoy various tourism information search and smart tourism–related services. However, due to the limited capacity of wireless networks, in peaking seasons, tourism area crowding in local areas could result in emergency and temporary wireless network congestion. While increasing infrastructure investment (e.g., densifying base stations) is desiring for peak seasons, it can be a waste of resource for significantly shrunk tourist arrival in off seasons. In response to the temporary network congestion offloading demand, this paper proposes an on-demand coverage solution based on unmanned aerial vehicle (UAV) base stations. Firstly, taking the air-to-ground channel characteristic into account, we define the effective coverage radius, based on which the optimal altitude of UAV BS is derived. Then, to tackle the inherent challenge of irregular tourist distribution issue in tourism areas, an automatic UAV BS deployment algorithm is designed to determine the minimal number of UAV BSs and their two-dimensional coordinates simultaneously. Simulation results show that the proposed solution could realize efficient UAV BS on-demand deployment.

The impact of climate change on the growth of European beech at optimal altitudes in the Republic of Srpska

Many studies have shown that small climate changes can strongly affect the forest trees growth rate, many times causing changes in species habitats. In general, drought is mentioned as the main problem, so it is necessary to carry out its identification and quantification to investigate its effects on forests in Republic of Srpska. This study aims to analyse the relationship between the growth of European beech (Fagus sylvatica L.) at optimal altitudes in the Republic of Srpska and its climate characteristics represented by the Forestry Aridity Index (FAI) and Ellenberg's climate quotient (EQ) for 1950-2015 timespan. FAI and EQ were calculated using climate data (temperature and precipitation) extracted from a gridded dataset (E-OBS). Sampling was carried out in two localities near Vlasenica and Mrkonjić Grad at 1050 and 1030 meters above sea level (m a.s.l.), sampling the cores from 15 dominant trees at each locality. Using the Pearson Correlation Analysis, a negative impact on tree rings width (TRW) with rising index values was identified. This is especially pronounced for the index values of the year prior to the ring formation. In general, stronger negative correlations between TRW and EQ are found for the locality near Mrkonjić Grad, while FAI index showed a greater negative impact on TRW for the locality near Vlasenica.

Collision Avoidance Modelling in Airline Traffic Based on the Change of Airplane Movements and Dynamic Clouds

An Air Traffic Controller (ATC) system aims to manage airline traffic to prevent collision of the airplane, called the Collision Avoidance (CA). The study on CA, called Conflict Detection and Resolution (CDR), becomes more critical as the airline traffic has grown each year significantly. Previous studies used optimization algorithms for CDR and did not involve the presence of cumulonimbus clouds. Many such clouds can be found in tropical regions like in Indonesia. Therefore, involving such clouds in the CDR optimization algorithms will be significant in Indonesia. We developed a CDR-based CA modelling that involves the Cumulonimbus (CB) clouds by considering three airplane maneuvers, i.e., Velocity, angle Turn and Altitude level Change (VTAC). Our optimization algorithm is developed based on a Mixed-Integer Programming (MIP) solver due to its efficiency. This proposed algorithm requires two input data, namely the initial airplane and cloud states input and the flight parameter such as velocity, angle and altitude levels. The outputs of our VTAC optimization algorithm are the optimum speed, altitude and angle turn of an airplane that is determined based on the currently calculated variables. Extensive experiments have been conducted to validate the proposed approach and the experiment results show that collisions between airplanes and clouds can be avoided with minimum change of the initial airplane velocity, angle and altitude levels. The VTAC algorithm produced longer distance to avoid collision between airplanes by at least 1 Nautical Mile (NM) compared to the VAC algorithm. The addition of angle in the VTAC algorithm has improved the result significantly.

The Performance Analysis of Spectrum Sharing Between UAV Enabled Wireless Mesh Networks and Ground Networks

Unmanned aerial vehicle (UAV) has the advantages of large coverage and flexibility, which could be applied in disaster management to provide wireless services to the rescuers and victims. When UAVs forms an aerial mesh network, line-of-sight (LoS) air-to-air (A2A) communications have long transmission distance, which extends the coverage of multiple UAVs. However, the capacity of UAV is constrained due to the multiple hop transmissions in aerial mesh networks. In this paper, spectrum sharing between UAV enabled wireless mesh networks and ground networks is studied to improve the capacity of UAV networks. Considering two-dimensional (2D) and three-dimensional (3D) homogeneous Poisson point process (PPP) modeling for the distribution of UAVs within a vertical range $\Delta \textit h$ , stochastic geometry is applied to analyze the impact of the height of UAVs, the transmit power of UAVs, the density of UAVs and the vertical range, etc., on the coverage probability of ground network user and UAV network user. Besides, performance improvement of spectrum sharing with directional antenna is verified. With the object function of maximizing the transmission capacity, the optimal altitude of UAVs is obtained. This paper provides a theoretical guideline for the spectrum sharing of UAV enabled wireless mesh networks, which may contribute significant value to the study of spectrum sharing mechanisms for UAV enabled wireless mesh networks.

Intelligent UAV Deployment for a Disaster-Resilient Wireless Network.

Deployment of unmanned aerial vehicles (UAVs) as aerial base stations (ABSs) has been considered to be a feasible solution to provide network coverage in scenarios where the conventional terrestrial network is overloaded or inaccessible due to an emergency situation. This article studies the problem of optimal placement of the UAVs as ABSs to enable network connectivity for the users in such a scenario. The main contributions of this work include a less complex approach to optimally position the UAVs and to assign user equipment (UE) to each ABS, such that the total spectral efficiency (TSE) of the network is maximized, while maintaining a minimum QoS requirement for the UEs. The main advantage of the proposed approach is that it only requires the knowledge of UE and ABS locations and statistical channel state information. The optimal 2-dimensional (2D) positions of the ABSs and the UE assignments are found using K-means clustering and a stable marriage approach, considering the characteristics of the air-to-ground propagation channels, the impact of co-channel interference from other ABSs, and the energy constraints of the ABSs. Two approaches are proposed to find the optimal altitudes of the ABSs, using search space constrained exhaustive search and particle swarm optimization (PSO). The numerical results show that the PSO-based approach results in higher TSE compared to the exhaustive search-based approach in dense networks, consuming similar amount of energy for ABS movements. Both approaches lead up to approximately 8-fold energy savings compared to ABS placement using naive exhaustive search.

Substantiation of the choice of the optimal UAV flight altitude for monitoring technological stresses for crops of winter rape

Crop monitoring using UAVs is becoming standard practice in scientific research due to the possibility of an operational examination of large fields with high data quality due to high-resolution images. The need for operational inspection of crops on an industrial scale requires a certain balance between the permissible image quality and the acceptable monitoring time due primarily to the number of UAVs and their energy. The newest and most relevant stress factor for Ukraine is technological stresses. The aim of the study is the optimal flight altitude for monitoring stresses of a technological nature. Field studies were carried out from September to November 2019 in the Boryspil region on industrial crops of winter rape. Monitoring was carried out using the Slantrange 3p complex. Stresses were recorded according to 2 parameters — the area of the dome and the abnormal coloration of the 2 lower leaves of red, yellow, and a mixture of these colors. The maximum quality of identification is achieved at the maximum resolution of the images, that is, the minimum height, however, the issues of UAV energy determine the maximum height and, accordingly, the flight speed for the UAV. Thus, the optimal compromise is between the determination accuracy and the production-appropriate flight parameters, that is, a lot of metric optimization is needed. As a generalized criterion, the criterion of consistent products was chosen, where the number of local optimization criteria is s = 3, and the weighting coefficients of the criteria are selected subjectively by experts. The proposed algorithm for choosing the optimal UAV flight altitude to identify the technological nature of the stress of winter rape crops will allow planning monitoring activities and justifying the choice of UAV parameters relative to the duration of its flight. The type of objective function used will allow specialists without specialized education in programming to solve the problem of multi-criteria optimization by its own weight coefficients. The proposed approach has no restrictions on the number of optimization parameters and the number of local optimality criteria and can be used when the user chooses his own indication indicators.

Channel characterization and performance analysis of unmanned aerial vehicle‐operated communication system with multihop radio frequency–free‐space optical link in dynamic environment

SummaryUnmanned aerial vehicles (UAVs) have been widely used in wireless communication in recent years and are a promising component of future wireless systems. UAVs are easily deployable and can provide reliable, robust, and cost‐effective communication to any desired location. However, the performance parameters of UAV cannot attain the desired level due to additional path loss caused by diffraction in non‐line of sight (NLOS) propagation during atmospheric turbulence. In this paper, UAV operated communication system with multihop radio frequency (RF)–free‐space optical (FSO) link is proposed. In order to provide better network connectivity and coverage, relays which also act as low altitude platform are configured between source and destination. These relays are modeled using RF and FSO technologies and also maintain decode and forward protocol and linear network coding. Based on this setup, communication channel is classified into three segments namely, ground to UAV, UAV to UAV, and UAV to ground channel. Initially, the optimal altitude of UAVs is derived using RF and FSO channel parameters for reliable system performance. The proposed model is verified using Monte Carlo simulation method, and the performance of the model is measured in terms of outage probability and symbol error rate, assuming that coherent detection takes place at receiver which employs M‐ary phase shift keying modulation techniques. Numerical results demonstrate that the proposed multihop RF–FSO link outperforms the relevant benchmark schemes for a given signal to noise ratio value.

Direct and Indirect Analysis of the Elevational Shift of Larch Budmoth Outbreaks Along an Elevation Gradient

Larch budmoth (LBM) periodically defoliates alpine stands of European larch during vast outbreaks occurring generally at 8-10 year intervals. LBM outbreaks recently declined and the ongoing global warming has been pointed out as a possible cause of this decline. We reconstructed the recent history of LBM outbreaks at different elevations along a larch altitudinal gradient in the French Alps using direct and indirect observations based on tree-ring width and density analysis, and compared it with local climatic data. We found that LBM outbreaks time-series were better reconstructed with latewood density than with ring width. We also found that there was a recent but limited altitudinal shift of LBM outbreaks from medium towards higher elevations. We suggest that this altitudinal shift is a consequence of the variable effect of the global warming at the different elevations. Winter warming is expected to affect differently the timing of LBM egg hatch as well as that of larch bud flush, larvae being at present susceptible to emerge whereas no needles are available as food at the former optimal altitude. A better synchronization between larch and LBM may exist at higher elevations.

Analysis of Existing Electrostatic Spraying Systems for UAV

The processing of agricultural crops using unmanned aerial vehicles is accompanied by the drift of the aerosol cloud under the influence of wind and the uneven density of droplet deposition on the surface of plants. We can improve the processing efficiency by implementing an electrostatic charging system for working fluid drops. (Research purpose) The research purpose is in preparing an analytical review of existing systems for electrostatic charging of working fluid droplets on unmanned aerial vehicles. (Materials and methods) Authors reviewed patents, scientific papers in the field of development, evaluation of the operation parameters and efficiency of the electrostatic spraying system of working fluid on unmanned aerial vehicles. The article gives criteria for the effectiveness of the electrostatic spraying system. (Results and discussion) Authors have described the main method of electrostatic charging of droplets, which has proven itself according to such criteria as safety, energy consumption and design simplicity. The article describes an electrostatic spraying system, the design and operating principle of which are the basis of modern systems for electric charging of working fluid drops installed on ground and aviation equipment. Authors found out the optimal flight altitude, which provides the highest density of working fluid drops on the treated surface. (Conclusions) The use of an electrostatic spraying system on unmanned aerial vehicles increases the density of droplets of sprayed liquid by 33 percent. The article shows that the use of nozzles with a fan-shaped spray torch reduces the distance of aerosol droplets drift in a crosswind by 1.5-2 times compared to nozzles with a cone-shaped spray torch. The electrostatic spraying system slightly increased the density of droplet deposition in the lower part of the plants (targets).

Minimization of aircraft fuel consumption subjected to arrival time constraint

PurposeThis paper aims to minimize aircraft fuel consumption during the cruise phase when the flight is subjected to a specific time of arrival for different weights and distances.Design/methodology/approachThe approach adopted herein uses sequential quadratic programming algorithm from MATLAB optimization toolbox, which includes a mathematical model of a jet airliner based on the Base of Aircraft Data as a function evaluator, to find out the impact of meet-time of arrival constraints on fuel consumption. The cruising speeds at predefined segments and the altitude are defined as the design variables.FindingsThe algorithm determines the optimum cruise altitudes and speeds for minimum fuel consumption in the case of no time constraints, also, for different time constraints where the flight time shall be reduced by increasing speed and lowering the altitude in most of the investigated cases.Practical implicationsThe algorithm computes the optimum speed and the altitude according to different flight scenarios with the meet-time of arrival constraints for minimum fuel consumption which affects the direct operating cost of the flight. The algorithm might greatly help in decision-making for the meet-time of arrival operations.Originality/valueDeveloping an algorithm to optimize the speed and the altitude of an aircraft based on weight and range for minimization of fuel consumption. It is a pioneer study in the literature that deals with the effect of meet-time constraints on fuel consumption.

Phosphate Solubilizing-based Peat Soil Carier Applied to Potato

Purpose : The indigenous phosphate solubilizing stored in peat soil as a carier is still a prospect as an ingredient of biological fertilizer, so it still needs to review how the indigenus phosphate solubilizing area of Tanjungsari, Sumedang worthy to be used as an ingredient Biological fertilizer.Research Method : The experiment was conducted at the Faculty of Agriculture Univeritas Winaya Mukti with the land type Andisol and the altitude of 850 m asL, carried out in March to June 2019. Environmental design using random draft group combination repeated 3 times with treatment consists of 13 treatments that are a type of phosphate solubilizing combined with a dose of peat soil carier. The data was analyzed further with Duncan’s test at 5%. Findings : Results showed that the Tanjungsari’s indigenus phosphate solubilizing with peat soil effect on the Phosphate is available on the soil, Phosphate total domain, potato shoot root ratio, number of the cropping bulbs, the weight of the tuber per plant and the weight per tuber, but has no effect on pH Soil, bacterial population, cation exchange capacity soils and absorption Phosphate in plants.Limitations : This research is done at medium place height where not the optimum altitude for potato.Value : Phosphate solubilizing bacteria indigenous from Tanjungsari Sumedang with carrier materials peat soil has the potential to be used organic fertilizer.

On Obtaining Energy-Optimal Trajectories for Landing of UAVs

The optimization issues connected to a landing task of an unmanned aerial vehicle are discussed in the paper, based on a model of a mini-class drone. Three landing scenarios are considered, including minimum-time landing, landing with minimum energy consumption, and planned landing. With the use of classical dynamic programming techniques, including the minimum principle of Pontryagin, as well as the calculus of variations, the optimal altitude reference trajectories are found, to form the altitude control system in such a way as to mimic the profile of the reference trajectory by the actual altitude of the UAV. The simulation results conducted with the use of the Simulink Support Package for Parrot Minidrones verify the correctness and effectiveness of the method, and open the research directions for further analysis, especially to tune altitude controller in a way, as to track the reference profile. Up to this point, optimization tasks considered in the literature, with respect to the drones, were connected to swarm formation optimization, optimization of the take-off process or landing process limited to optimal path planning. This paper thus considers a new topic in the field.

Microbial Component Detection in Enceladus Snowing Phenomenon

Enceladus is an attractive place to look for signs of life thanks to liquid water and the availability of energy. Recent research has proven that the ejected material of Enceladus south pole consists of water vapor, water ice, carbon dioxide, methane and molecular hydrogen. Possible similarities of physical and chemical conditions between Enceladus ocean bottom and the carbonate mineral matrix of actively venting chimneys of the Lost City Hydrothermal Field give an opportunity to create a mathematical model of microbial ascent process through the ice shell. In this study we present first results of particle in-cell kinetic simulations of microbial distance through 10 km deep ocean. We have obtained results for microbial component—Methanosarcinales sp. analogue—characterized by 6.6 pg mass and 2.0 μm diameter distribution in Enceladus plumes. We have assumed 0.1 W m−2 heating process, 5 km ice shell and cells concentration near ocean bottom 105 cells/mL. We have confirmed assumption of Porco research team about cells concentration near ocean surface about 104 cells/mL and vertical density diversity in plumes. We have found that the optimal altitude for microbial component detection is less than 1.0 km and that in-situ measurements done previously by Cassini mass spectrometer and proposed for Enceladus Orbiter mission 50 km altitude would be ineffective.

Hypoxic Training Is Beneficial in Elite Athletes.

There is no doubt that many hypoxic conditions or prolonged exposures to altitude result in “biological costs of hypoxic adaptations that outweigh their benefits” (1), particularly in endurance athletes exposed to a) exercise-induced arterial hypoxemia leading to a larger decrease in VO2max and aerobic endurance; b) increased sympathetic activity and decreased baroreflex sensitivity; and c) increased pulmonary arterial pressure. There is also no doubt that sleeping in moderate altitude (2000-3000 m) as performed by the athletes using either live high-train high (LHTH) or live high-train low (LHTL) methods leads to periodic breathing, intermittent hypoxia (IH) and increase in desaturation periods; e.g. 3% oxygen desaturation index, but to a larger extent in hypobaric hypoxia (HH, real altitude) than in normobaric hypoxia (NH, simulated altitude), as shown at 2250 m (2). The three main questions debated in the present contrasting perspective are however different: 1. Are there any evidences showing if the “counteracting maladaptation” (reported above) outweigh the benefits of the different hypoxic methods at short- or long-term in elite athletes? ; 2. Are there any robust data supporting that hypoxic training is beneficial in elite athletes? ; 3. Contradictory, are there robust data showing that hypoxic training is not beneficial in elite athletes?

AI-Aided Downlink Interference Control in Dense Interference-Aware Drone Small Cells Networks

Recently, drone small cells (DSCs) has been brought into significant focus, which is the one key enabler for potentially facilitating terrestrial wireless communication systems. Meanwhile, in ultra-dense unmanned networks, artificial intelligence (AI) has been a useful and efficient tool for control and management of the multi-agents. This paper investigates a downlink interference control problem in ultra-dense unmanned networks with AI-aided approach, that each DSC can adjust its altitude to increase the data-rate. This problem is formulated as a mean field game (MFG) framework, an AI-aided method to make decisions. In this framework, each DSC controls its velocity to minimize the cost over a period, where the cost function is composed by the data-rate and height adjusting consumption. Meanwhile, in this model, we adopt the mean-field approximation (MFA) approach to derive the interference introduced from a large number of DSCs. Besides, the control strategy is described and explained by using the related Hamilton-Jacobi-Bellman (HJB) and Fokker-Planck-Kolmogorov (FPK) equations, respectively. Thus, a finite difference algorithm is proposed to solve the coupled partial differential equations, which can obtain the optimal altitude control strategy. The algorithm outputs show the optimal behaviors of DSCs in different environment scenarios. In additon, the simulation results verify that the proposed control strategy has better average signal to interference plus noise ratio (SINR) compared with the baseline method.

Optimal Altitude Selection of Aerial Base Stations to Maximize Coverage and Energy Harvesting Probabilities: A Stochastic Geometry Analysis

This paper provides radio frequency (RF) energy harvesting and coverage probability analysis using stochastic geometry in a two-hop communication network. In the first hop, terrestrial base stations (TBSs) transmit RF energy and data to the aerial base stations (ABSs) and in the second hop, ABSs forward the data to the user. Numerical results show that the energy harvesting and coverage probabilities can be maximized at almost the same altitude of the ABSs with respect to the TBSs height for low TBSs densities. However, as the density of the backhaul nodes and the energy harvesting sub-timeslot increases, energy harvesting probability improves while coverage probability monotonically decreases by increasing the ABSs height.

Design and Analysis of UAV-Assisted Relaying With Simultaneous Wireless Information and Power Transfer

We consider a two-phase decode-and-forward (DF) relay network assisted by an unmanned aerial vehicle (UAV), where the UAV performs energy harvesting and information decoding simultaneously with a power splitting (PS) receiver structure. For the network, we optimize the PS and time allocation (TA) factors to minimize the outage probability in transferring the data from a source to a destination suffering from blockages in the direct link. The optimal solution is found in two steps, optimization of the PS factor for given TA and then optimization of the TA factor using the conditionally optimized PS factor given in a closed-form. To reduce the complexity of the optimal method, we next propose a suboptimal method using a fixed TA determined by the transmission rate only and a fixed PS ffactor given by a function of the average power of the UAV-to-destination channel. The outage probability of the proposed method is analyzed in a generalized UAV channel model including path-loss, shadowing, and Nakagami-m fading, which is shown to agree with the simulation results and is close to the optimal performance. In addition, the optimal UAV position is investigated in various channel environments, which reveals that the optimal altitude depends on the deployment scenarios and the optimal ground position is the center-point between the source and destination in general.

The Spatial Pattern of Rice Productivity Using Sentinel-2A Image in Cariu and Tanjungsari District, Bogor Regency

Rice is known as substantial main foodstuffs of Indonesian people. According to the Report from Indonesia Centrer of statistic (BPS), of- West Java Province 2018, Bogor Region is one of lower-rice productions which was shown by decreasing value approximately 26,307 ton between 2014 and 2015. The increasing efforts of rice productivity is required to estimate and observe a rice-grain supplying in the market, especially in Cariu and Tanjungsari as the primary and specific city of rice production in Bogor Region. To gain an accurate data, remote sensing method is applied. The using of sentinel-2A image processing which has 10 m of spatial resolution is recommended to see the rice planting phase based on the age of planting. The study aims to analyze the spatial studying of rice production using Sentinel-2A image processing with Normalize Difference Vegetation Index (NDVI) method for to determine the age of rice plants starting from the beginning of planting to the end of the harvest and also help estimate the productivity of rice paddies. The results show that rice production estimation which is planted in the altitude of under 100 masl (mean sea level) have value 5,52 ton/ha, to the optimum altitude on the range of 100-500 masl the productivity increase become 6,31 ton/ha, and back down on the altitude more than 500 masl equal to 5,34 ton/ha.

A Unified Spatial Framework for UAV-Aided MmWave Networks

For unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) networks, we propose a unified three-dimensional (3D) spatial framework in this paper to model a general case that uncovered users send messages to base stations via UAVs. More specifically, the locations of transceivers in downlink and uplink are modeled through the Poisson point processes and Poisson cluster processes (PCPs), respectively. For PCPs, Matern cluster and Thomas cluster processes, are analyzed. Furthermore, both 3D blockage processes and 3D antenna patterns are introduced for appraising the effect of altitudes. Based on this unified framework, several closed-form expressions for the coverage probability in the uplink and downlink, are derived. By investigating the entire communication process, which includes the two aforementioned phases and the cooperative transmission between them, tractable expressions of system coverage probabilities are derived. Next, three practical applications in UAV networks are provided as case studies of the proposed framework. The results reveal that the impact of thermal noise and non-line-of-sight mmWave transmissions is negligible. In the considered networks, mmWave outperforms sub-6 GHz in terms of the data rate, due to the sharp direction beamforming and large transmit bandwidth. Additionally, there exists an optimal altitude of UAVs, which maximizes the system coverage probability.

The optimal survey area of the semi-airborne TEM method

The semi-airborne transient electromagnetic method (TEM) has been widely used in resource exploration and other fields due to its high efficiency, strong adaptability to the complex environment and high resolution. However, the conventional semi-airborne electromagnetic method continues to use the survey area of the grounded-wire TEM method. Compared with the existing ground-based TEM method, the semi-airborne TEM method is more sensitive to signal intensity because observed data is easily affected by noise for receiving position in the air. Therefore, it's unreasonable to consider only signal intensity or sensitivity related to offset in survey area. To obtain more suitable area, we discuss the distribution of the transient electromagnetic field with electrical source as well as the attenuation characteristics of the signal at different flight altitude through the forward modeling. Then, we obtain the sensitive area and flight altitude applied by the error analysis method in typical models. Finally, we describe a method what is herein dubbed the fuzzy comprehensive evaluation, which greatly reflects the membership degree of the evaluation object from different single factors to each level of fuzzy subset. Therefore, we use this method to get the optimal survey area and flight altitude under different noise levels. In low noise level, the signal intensity and sensitivity account for 33.3% and 66.7% respectively in selecting the optimum area and altitude, resulting in that the optimal area and flight altitude are coincides with the sensitive area and altitude better. While in the area filled with noise, the most area of strongest signal intensity is considered the optimal area and altitude. A field example shows that the aforementioned method can be well resolved in identifying survey lines and improving data quality.