Efficient 3D Placement of a UAV Using Particle Swarm Optimization

Unmanned aerial vehicles (UAVs) can be used as aerial wireless base stations when cellular networks go down. Prior studies on UAV-based wireless coverage typically consider an Air-to-Ground path loss model, which assumes that the users are outdoor and they are located on a 2D plane. In this paper, we propose using a single UAV to provide wireless coverage for indoor users inside a high-rise building under disaster situations (such as earthquakes or floods), when cellular networks are down. We assume that the locations of indoor users are uniformly distributed in each floor and we propose a particle swarm optimization algorithm to find an efficient 3D placement of a UAV that minimizes the total transmit power required to cover the indoor users.Comment: 6 pages, 7 figure

Few-mode optical fiber surface plasmon resonance sensor with controllable range of measured refractive index

A few-mode optical fiber surface plasmon resonance sensor with graphene layer is investigated, firstly, with the aim of studying the behavior of the guided modes and, secondly, with the aim of determining the range of the measured refractive index for some selected few-mode fibers. The results show that as the number of modes propagated in the fiber increases, the maximum sensitivity of a particular mode decreases while the range of the measured refractive index of that mode increases. Also, it is shown that the range can be easily tuned with sensitivity consideration by only adjusting the operating wavelength without any modification of the sensor, which is desirable from practical point of view. In addition, it is shown that the core diameter of the fiber should be chosen according to sensitivity and range needing, where a compromise between them must be found. The study presented in this paper can significantly help in developing new sensing techniques, such as multi-parameter sensing, by monitoring the various responses of the modes. Also, it can be used to customize the sensor for specific sensing applications in various fields, especially to measure refractive indices in subranges of 1.38 to 1.46

Adaptive Control of IoT/M2M Devices in Smart Buildings using Heterogeneous Wireless Networks

With the rapid development of wireless communication technology, the Internet of Things (IoT) and Machine-to-Machine (M2M) are becoming essential for many applications. One of the most emblematic IoT/M2M applications is smart buildings. The current Building Automation Systems (BAS) are limited by many factors, including the lack of integration of IoT and M2M technologies, unfriendly user interfacing, and the lack of a convergent solution. Therefore, this paper proposes a better approach of using heterogeneous wireless networks consisting of Wireless Sensor Networks (WSNs) and Mobile Cellular Networks (MCNs) for IoT/M2M smart building systems. One of the most significant outcomes of this research is to provide accurate readings to the server, and very low latency, through which users can easily control and monitor remotely the proposed system that consists of several innovative services, namely smart parking, garden irrigation automation, intrusion alarm, smart door, fire and gas detection, smart lighting, smart medication reminder, and indoor air quality monitoring. All these services are designed and implemented to control and monitor from afar the building via our free mobile application named Raniso which is a local server that allows remote control of the building. This IoT/M2M smart building system is customizable to meet the needs of users, improving safety and quality of life while reducing energy consumption. Additionally, it helps prevent the loss of resources and human lives by detecting and managing risks.Comment: Accepted in IEEE Sensors Journa

Efficient Deployment of Multi-UAVs in Massively Crowded Events

In this paper, the efficient 3D placement of UAV as an aerial base station in providing wireless coverage for users in a small and large coverage area is investigated. In the case of providing wireless coverage for outdoor and indoor users in a small area, the Particle Swarm Optimization (PSO) and K-means with Ternary Search (KTS) algorithms are invoked to find an efficient 3D location of a single UAV with the objective of minimizing its required transmit power. It was observed that a single UAV at the 3D location found using the PSO algorithm requires less transmit power, by a factor of 1/5 compared to that when using the KTS algorithm. In the case of providing wireless coverage for users in three different shapes of a large coverage area, namely square, rectangle and circular regions, the problems of finding an efficient placement of multiple UAVs equipped with a directional antenna are formulated with the objective to maximize the coverage area and coverage density using the Circle Packing Theory (CPT). Then, the UAV efficient altitude placement is formulated with the objective of minimizing its required transmit power. It is observed that the large number of UAVs does not necessarily result in the maximum coverage density. Based on the simulation results, the deployment of 16, 19 and 26 UAVs is capable of providing the maximum coverage density of 78.5%, 82.5% and 80.3% for the case of a square region with the dimensions of 2 km × 2 km, a rectangle region with the dimensions of 6 km × 1.8 km and a circular region with the radius of 1.125 km, respectively. These observations are obtained when the UAVs are located at the optimum altitude, where the required transmit power for each UAV is reasonably small

Efficient Placement of an Aerial Relay Drone for Throughput Maximization

Unmanned aerial vehicle (UAV) communication can be used in overcrowded areas and either during or postdisaster situations as an evolving technology to provide ubiquitous connections for wireless devices due to its flexibility, mobility, and good condition of the line of sight channels. In this paper, a single UAV is used as an aerial relay node to provide connectivity to wireless devices because of the considerable distance between wireless devices and the ground base station. Specifically, two path loss models have been utilized; a cellular-to-UAV path loss for a backhaul connection and an air-to-ground path loss model for a downlink connection scenario. Then, the tradeoff introduced by these models is discussed. The problem of efficient placement of an aerial relay node is formulated as an optimization problem, where the objective is to maximize the total throughput of wireless devices. To find an appropriate location for a relay aerial node that maximizes the overall throughput, we first use the particle swarm optimization algorithm to find the drone location; then, we use three different approaches, namely, (1) the equal power allocation approach, (2) water filling approach, and (3) modified water filling approach to maximize the total users’ throughput. The results show that the modified water filling outperforms the other two approaches in terms of the average sum rate of all users and the total number of served users. More specifically, in the best-case scenario, it was observed that the average sum rate of the modified water filling is better than the equal power allocation and ensuring 100% coverage. In contrast, the water filling provides a very close average sum rate to the modified water filling, but it only provides a 28% user coverage

Few-mode optical fiber surface plasmon resonance sensor with controllable range of measured refractive index

A few-mode optical fiber surface plasmon resonance sensor with graphene layer is investigated, firstly, with the aim of studying the behavior of the guided modes and, secondly, with the aim of determining the range of the measured refractive index for some selected few-mode fibers. The results show that as the number of modes propagated in the fiber increases, the maximum sensitivity of a particular mode decreases while the range of the measured refractive index of that mode increases. Also, it is shown that the range can be easily tuned with sensitivity consideration by only adjusting the operating wavelength without any modification of the sensor, which is desirable from practical point of view. In addition, it is shown that the core diameter of the fiber should be chosen according to sensitivity and range needing, where a compromise between them must be found. The study presented in this paper can significantly help in developing new sensing techniques, such as multi-parameter sensing, by monitoring the various responses of the modes. Also, it can be used to customize the sensor for specific sensing applications in various fields, especially to measure refractive indices in subranges of 1.38 to 1.46

Flipped classroom model and self-efficacy in an Iranian English as a foreign language context: A gender-based study

This study aimed to investigate the impact of the flipped classroom model on students’ self-efficacy and the difference in self-efficacy between males and females using this model. In order to accomplish this, 66 advanced participants were selected from a private English language institute. They were divided into two equal groups, namely experimental (flipped classroom) and control (traditional) group. The students’ self-efficacy was scored before and after the intervention with the Self-Efficacy Survey. The results indicated an increase in their average self-efficacy score with the flipped classroom while the traditional classroom decreased their average score. When the genders were analyzed separately, the males demonstrated a decrease in self-efficacy while the females indicated an increase while utilizing the flipped classroom. In light of these results, some recommendations have been made

Robust graph‐based localization for industrial Internet of things in the presence of flipping ambiguities

Abstract Localisation of machines in harsh Industrial Internet of Things (IIoT) environment is necessary for various applications. Therefore, a novel localisation algorithm is proposed for noisy range measurements in IIoT networks. The position of an unknown machine device in the network is estimated using the relative distances between blind machines (BMs) and anchor machines (AMs). Moreover, a more practical and challenging scenario with the erroneous position of AM is considered, which brings additional uncertainty to the final position estimation. Therefore, the AMs selection algorithm for the localisation of BMs in the IIoT network is introduced. Only those AMs will participate in the localisation process, which increases the accuracy of the final location estimate. Then, the closed‐form expression of the proposed greedy successive anchorization process is derived, which prevents possible local convergence, reduces computation, and achieves Cramér‐Rao lower bound accuracy for white Gaussian measurement noise. The results are compared with the state‐of‐the‐art and verified through numerous simulations