Drones, Volume 2, Issue 3 (September 2018) – 10 articles

Multi-Unmanned Aerial Vehicle (UAV) enabled Wireless Sensor Networks (WSNs) provide a wide range of applications, covering civilian and military expeditions along with geographical navigation, control, and reconnaissance. The coordinated networks formed between the UAVs and the WSNs help in enhancing the issues related to quality as well as coverage. The overall coverage issues result in starvation as an effect of long waiting time for the nodes, while forwarding the traffic. The coverage problem can be resolved by an intelligent choice of UAV way-points. Therefore, a specialized UAV mobility model is required which takes into account the topological structure as well as the importance of strategic locations to fix UAV way-points and decide the data transmission paradigm. To resolve this problem, a novel mobility model is proposed, which takes into account the attraction factor for setting up the way-points for UAV movements. The model is capable of deciding between the locations which result in more coverage, increased throughput with lesser number of UAVs employed, as justified by the simulation results and comparative evaluations. Full article

Stabilizing the Unmanned Aircraft Systems (UAS) under complex environment including system uncertainties, unknown noise and/or disturbance is so challenging. Therefore, this paper proposes an adaptive neural network based intelligent control method to overcome these challenges. Based on a class of artificial neural network, named Radial Basis Function (RBF) networks an adaptive neural network controller is designed. To handle the unknown dynamics and uncertainties in the system, firstly, we develop a neural network based identifier. Then, a neural network based controller is generated based on both the identified model of the system and the linear or nonlinear controller. To ensure the stability of the system during its online training phase, the linear or nonlinear controller is utilized. The learning capability of the proposed intelligent controller makes it a promising approach to take system uncertainties, noises and/or disturbances into account. The satisfactory performance of the proposed intelligent controller is validated based on the computer based simulation results of a benchmark UAS with system uncertainties and disturbances, such as wind gusts disturbance. Full article

This paper presents experimentation carried out at the Roman Republican city of La Caridad (Teruel, Spain), where different tools have been applied to obtain multispectral and thermal aerial images to enhance detection of archaeological cropmarks. Two different drone systems were used: a Mikrokopter designed by Tecnitop SA (Zaragoza, Spain) and an eBee produced by SenseFly Company (Cheseaux-sur-Lausanne, Switzerland). Thus, in this study, we have combined in-house manufacturing with commercial products. Six drone sensors were tested and compared in terms of their ability to identify buried remains in archaeological settlements by means of visual recognition. The sensors have different spectral ranges and spatial resolutions. This paper compares the images captured with different spectral range sensors to test the potential of this technology for archaeological benefits. The method used for the comparison of the tools has been based on direct visual inspection, as in traditional aerial archaeology. Through interpretation of the resulting data, our aim has been to determine which drones and sensors obtained the best results in the visualization of archaeological cropmarks. The experiment in La Caridad therefore demonstrates the benefit of using drones with different sensors to monitor archaeological cropmarks for a more cost-effective assessment, best spatial resolution and digital recording of buried archaeological remains. Full article

The application of remote sensing methods to assess crop vigor and yields has had limited applications in Sub-Saharan Africa (SSA) due largely to limitations associated with satellite images. The increasing use of unmanned aerial vehicles in recent times opens up new possibilities for remotely sensing crop status and yields even on complex smallholder farms. This study demonstrates the applicability of a vegetation index derived from UAV imagery to assess maize (Zea mays L.) crop vigor and yields at various stages of crop growth. The study employs a quadcopter flown at 100 m over farm plots and equipped with two consumer-grade cameras, one of which is modified to capture images in the near infrared. We find that UAV-derived GNDVI is a better indicator of crop vigor and a better estimator of yields—r = 0.372 and r = 0.393 for mean and maximum GNDVI respectively at about five weeks after planting compared to in-field methods like SPAD readings at the same stage (r = 0.259). Our study therefore demonstrates that GNDVI derived from UAV imagery is a reliable and timeous predictor of crop vigor and yields and that this is applicable even in complex smallholder farms in SSA. Full article

The ever-increasing demand for flexible and portable communications has led to a rapid evolution in networking between unmanned aerial vehicles (UAVs) often referred to as flying ad-hoc networks (FANETs). However, due to the exclusive characteristics of UAVs such as high mobility, frequent topology change and 3D space movement, make routing a challenging task in FANETs. Due to these characteristics, designing new routing protocols for FANETs is quite difficult. In the literature study of FANETs, a variety of traditional ad-hoc networking protocols have been suggested and tested for FANETs to establish an efficient and robust communication among the UAVs. In this context, topology-based routing is considered the most significant approach for solving the routing issues in FANETs. Therefore, in this article we specifically focus on topology-based routing protocols with the aim of improving the efficiency of the network in terms of throughput, end-to-end delay, and network load. We present a brief review of the most important topology-based routing protocols in the context of FANETs. We provide them with their working features for exchanging information, along with the pros and cons of each protocol. Moreover, simulation analyses of some of the topology-based routing protocols are also evaluated in terms of end-to-end delay, throughput and network load the using optimized network engineering tools (OPNET) simulator. Furthermore, this work can be used as a source of reference for researchers and network engineers who seek literature that is relevant to routing in FANETs. Full article

In many incidents involving amateur drones (ADr), the big challenge is to quickly deploy a surveillance system that countermeasures the threat and keeps track of the intruders. Depending on the area under concern, launching a single surveillance drone (SDr) to hunt the intruder is not efficient, but employing multiple ones can cope with the problem. However, in order to make this approach feasible, an easy to use mission setup and control station for multiple SDr is required, which by its turn, requires a communication infrastructure able to handle the connection of multiple SDr among themselves and their ground control and payload visualization station. Concerning this Issue, this paper presents a proposal of a network infrastructure to support the operation of multiple SDr and its practical deployment. This infrastructure extends the existing Micro Air Vehicle Link (MAVLink) protocol to support multiple connections among the SDrs and between them and a ground control station. Encouraging results are obtained, showing the viability of this proposed protocol extension. Full article

This work aims to study and compare different range finders applied to altitude sensing on a rotating wings UAV. The specific application is the altitude maintenance for the fluid deployment valve aperture control in an unmanned pulverization aircraft used in precision agriculture. The influence of a variety of parameters are analyzed, including the tolerance for crop inconsistencies, density variations and intrinsic factors to the process, such as the pulverization fluid interference in the sensor’s readings, as well as their vulnerability to harsh conditions of the operation environment. Filtering and data extraction techniques were applied and analyzed in order to enhance the measurement reliability. As a result, a wide study was performed, enabling better decision making about choosing the most appropriate sensor for each situation under analysis. The performed data analysis was able to provide a reliable baseline to compare the sensors. With a baseline set, it was possible to counterweight the sensors errors and other factors such as the MSE for each environment to provide a summarized score of the sensors. The sensors which provided the best performance in the used metrics and tested environment were Lightware SF11-C and LeddarTech M16. Full article

Widespread use of small unmanned aircraft systems is becoming prominent in the US. From structural health monitoring to journalism, small unmanned aerial systems (sUAS) are allowing people to gain a view of their surroundings and conduct their jobs in ways like never before. With this come many ethical concerns that must be addressed before the sight of a sUAS flying overhead is a widely acceptable occurrence to a majority of the population. Currently, UAS operations used in civil airspace are governed by the Federal Aviation Administration (FAA) Part 107 rules, but these regulations do not address certain ethical considerations. This paper will use the concept of a value model to quantify these ethical concerns so that they may be encoded into the design of a UAS and evaluation of missions before the missions are conducted. This could prove valuable in addressing the ethical challenges that are faced when implementing unmanned aerial systems (UAS) operations into the airspace, especially when UASs are in airspace in densely populated areas. Full article

In the reported study, various aspects of dimethyl ether/hydrogen combustion in a Reactivity Controlled Compression Ignition (RCCI) engine are numerically evaluated using Reynolds Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES). Early direct injection and mixture propagation were also explored, along with peculiaritis of dimethyl ether combustion modeling. The numerical models are validated using available experimental results of a partially premixed dimethyl ether jet flames and an optically accessible internal combustion engine with direct hydrogen injection. LES showed more predictive results in modeling both combustion and mixture propagation. The same models were applied to a full engine cycle of an RCCI engine with stratified reactivity, to gain phenomenological insight into the physical processes involved in stratified reactivity combustion. We showed that 3D and turbulence considerations had a great impact on simulation results, and the LES was able to capture the pressure oscillations typical for this type of combustion. Full article

Yield estimates and yield gap analysis are important for identifying poor agricultural productivity. Remote sensing holds great promise for measuring yield and thus determining yield gaps. Farming systems in sub-Saharan Africa (SSA) are commonly characterized by small field size, intercropping, different crop species with similar phenologies, and sometimes high cloud frequency during the growing season, all of which pose real challenges to remote sensing. Here, an unmanned aerial vehicle (UAV) system based on a quadcopter equipped with two consumer-grade cameras was used for the delineation and classification of maize plants on smallholder farms in Ghana. Object-oriented image classification methods were applied to the imagery, combined with measures of image texture and intensity, hue, and saturation (IHS), in order to achieve delineation. It was found that the inclusion of a near-infrared (NIR) channel and red–green–blue (RGB) spectra, in combination with texture or IHS, increased the classification accuracy for both single and mosaic images to above 94%. Thus, the system proved suitable for delineating and classifying maize using RGB and NIR imagery and calculating the vegetation fraction, an important parameter in producing yield estimates for heterogeneous smallholder farming systems. Full article