Microservices for autonomous UAV inspection with UAV simulation as a service

As in traditional software development, non-functional requirements play also a crucial role in service-oriented development. Non-functional requirements are spread across the entire service-oriented system or within individual services and cannot be allocated to one specific system / service artefact (such as a package, component). This makes them often more difficult to handle than functional requirements. The specifics of service-oriented architectures (in particular highly distributed services) bring up additional difficulties. In this paper, we present a taxonomy for non-functional requirements in a service-oriented context. The taxonomy implements three main categories of non-functional requirements: process requirements, non-functional external requirements, and non-functional service requirements. The taxonomy can be applied with individual services as well as with a service-based system as a whole. This taxonomy is considered as a starting point and check list when handling non-functional issues in service-oriented and particularly highly distributed environments.

With the continuous expansion of the grid scale and the development of artificial intelligence, UAV inspection is gradually replacing manual inspections and has become a mainstream of transmission line inspections by its high efficiency, low cost and high safety, which has greatly improved the inspection efficiency and inspection accuracy of transmission lines. However, the existing UAV inspections mainly rely on manual methods, requiring staff to operate and perform a lot of interventions in the field. The operating specifications are not uniform, which brings a lot of difficulties to the subsequent intelligent identification. Therefore, this paper proposes an autonomous transmission line UAV inspection system based on the improved yolov4. First, a priori box is set through K-means clustering to enhance the size adaptability, and the improved yolov4 could identify the key structure of the transmission tower. Second, the system could move the PTZ to place the relevant structure in the center of the image to complete the collection of image information. The test results show that the system can collect relevant information of transmission line towers in a standardized manner, improve the accuracy of image collection, and expand the scope of application of autonomous drone inspections, and provide a new direction for subsequent intelligent inspections.

Multiuser collaborative work in virtual environment based CASE tool

In this paper we present a method for sharing interactive and dynamic 3D models that are collaboration-unaware, i.e., models that have not been designed to be used by multiple users at the same time. This functionality is an essential requirement for the inclusion of arbitrary 3D models, as generated by standard CAD or animation software, into teleconferencing sessions. A key aim of this work is to show that a large part of the required functionality can be developed in a way so that it is reusable for other applications such as shared whiteboards or networked computer games. Our method therefore consists of both an application dependent part that handles the specific tasks required for sharing 3D models, and of a number of generic services such as synchronization, scalable support for latecomers, and the ability to record and replay sessions. The generic services are based on an abstract media model and the RTP/I application level protocol for distributed interactive media. Any other application for a medium that shares this model and that uses RTP/I may reuse these generic services. We have implemented a prototype called TeCo3D demonstrating the feasibility of our approach.

Owing to the rise in cyber crime in cloud computing systems, cloud forensics has gained a lot of interest in the research community. Cloud forensic investigations differ from traditional forensic investigations due to the variability in architecture, lack of standardisation, distributed nature of cloud artefacts, scattered evidences and so on. The existing digital forensic tools cannot address these issues directly. The major challenge in cloud forensics is the identification and acquisition of artefacts. We propose a tool for forensic acquisition of artefacts on cloud systems. Our tool considers various artefacts such as cloud infrastructure logs, snapshots and volumes in addition to virtual disk and memory images. In this paper, we discuss the functional and non-functional requirements considered by our cloud forensic acquisition tool. We have implemented our solution on Openstack private IaaS cloud test bed.

This article discusses the main advantages and challenges of adopting microservices in cloud computing. The microservices architecture allows software developers to build a distributed application as a set of independent components that work together. This model isn't new, but, applied in cloud systems, it increases datacenter scalability and reliability. The authors discuss available technologies for deploying and controlling microservices-based application architectures in the cloud.

An uncountable number of services are deployed over cloud platforms and provided to millions of consumers. As this paradigm spreads over, the quality of provided services becomes a primary concern. Testing helps in making software reliable, but it has been overlooked for cloud. In this paper, we present a method for the robustness testing of software platforms for IaaS cloud. The method stresses the importance of considering the state for these systems, which are characterized by phase-based interactions of many software components with multiple concurrent users. Applied to a real cloud platform, the method exposes failures hard to uncover with common robustness testing approaches.

To address the challenges of low automation and poor adaptability to complex environments in power grid UAV inspections, this study analyzes the architecture and operational constraints of intelligent UAV inspection systems, clarifying optimization goals in terms of efficiency, safety, and intelligence. A closed-loop autonomous flight control method is proposed, integrating high-precision target recognition, dynamic path planning, and reinforcement learning–based optimization. Furthermore, a Transformer-based global obstacle perception and risk assessment approach is designed to construct a holistic “perception–decision–control” technical framework. Field experiments demonstrate that the proposed strategy significantly enhances flight path planning efficiency, obstacle recognition accuracy, and operational safety. The results provide scalable technical support for advancing the digital transformation of power grids and promoting the development of new-type power systems.

Overhead transmission line corridor detection is important to ensure the safety of power facilities. Frequent and uncertain changes in the transmission line corridor environment requires an efficient and autonomous UAV inspection system, whereas the existing UAV-based inspection systems has some shortcomings in control model and ground clearance measurement. For one thing, the existing manual control model has the risk of striking power lines because it is difficult for manipulators to judge the distance between the UAV fuselage and power lines accurately. For another, the ground clearance methods based on UAV usually depend on LiDAR (Light Detection and Ranging) or single-view visual repeat scanning, with which it is difficult to balance efficiency and accuracy. Aiming at addressing the challenging issues above, a novel UAV inspection system is developed, which can sense 3D information of transmission line corridor by the cooperation of the dual-view stereovision module and an advanced embedded NVIDIA platform. In addition, a series of advanced algorithms are embedded in the system to realize autonomous control of UAVs and ground clearance measurement. Firstly, an edge-assisted power line detection method is proposed to locate the power line accurately. Then, 3D reconstruction of the power line is achieved based on binocular vision, and the target flight points are generated in the world coordinate system one-by-one to guide the UAVs movement along power lines autonomously. In order to correctly detect whether the ground clearances are in the range of safety, we propose an aerial image classification based on a light-weight semantic segmentation network to provide auxiliary information categories of ground objects. Then, the 3D points of ground objects are reconstructed according to the matching points set obtained by an efficient feature matching method, and concatenated with 3D points of power lines. Finally, the ground clearance can be measured and detected according to the generated 3D points of the transmission line corridor. Tests on both corresponding datasets and practical 220-kV transmission line corridors are conducted. The experimental results of different modules reveal that our proposed system can be applied in practical inspection environments and has good performance.

Assisting elderly individuals in indoor environments is crucial, as they often encounter mobility and safety challenges. Autonomous Unmanned Aerial Vehicles (UAVs) navigation offers a transformative solution, significantly enhancing safety, efficiency, and quality of life. These UAVs can perform tasks such as monitoring, delivering essential items, and responding to emergencies, providing invaluable support and promoting greater independence for elderly individuals. To achieve effective assistance, autonomous UAV navigation relies on robust path planning with obstacle avoidance to ensure optimal performance. A newly developed path planning, based on a new hybrid Water Cycle Algorithm (WCA), stands out by addressing the challenge of avoiding obstacles while adhering to non-holonomic constraints and conserving energy in complex, cluttered indoor environments. In Population-Based Algorithms (PBAs), the initial population plays a crucial role, as it greatly impacts the algorithm’s efficiency in exploring the search space and its rate of convergence. The new developed hybrid algorithm, called WCA-HS, is based on using the Harmony Search (HS) algorithm to identify the optimal initial population for the WCA. The results indicate that the hybrid WCA-HS outperforms classical WCA and other metaheuristic algorithms, such as HS, Firefly Algorithm (FA), Cuckoo Search (CS), Genetic Algorithm (GA), Differential Evolution (DE), Ant Colony Optimization (ACO), and Artificial Bee Colony (ABC), over 20 independent runs, highlighting the effectiveness of the population initialization technique. Additionally, the developed indoor path planning system was evaluated in highly cluttered and low-light environments, showcasing its robustness and real-world applicability, making it highly effective for assisting elderly individuals in complex indoor environments.

Due to mobile devices' growing presence in our daily routine, mobile applications are becoming increasingly complex. They require more powerful processing capability and more extensive data storage, which characterizes a challenge when computational constraints of these devices are taken into account. Several software infrastructures proposed to help the development of mobile applications with data offloading features. However, they lack essential features for data offloading, such as configurable data synchronization policy models, privacy mechanisms for the offloaded data, and scalability and performance analyses. This work presents DOP, a solution to assist the development of mobile applications that use data migration, including contextual data, from mobile devices to a remote environment, based on a microservice architecture. The data offloading technique enables data migration into a remote environment, allowing (i) storage savings on the mobile device and (ii) sharing data among users. The experiments on DOP showed benefits in storage savings on mobile devices and new possibilities for inferring situations based on shared data from multiple users.

Complex service-oriented networked applications can be built in a flexible way by appropriate composition of individual services. Services are self-contained pieces of functionality that reside in remote nodes in the network and that communicate only via the exchange of messages. Service composition must be done in compliance with the application-level requirements i.e., quality of service (QoS) constraints. In this way, not only data dependencies must be satisfied but also other non-functional execution requirements must be considered (i.e., resource limitations and timing properties). This paper describes the structure of service-based applications, and it deepens in the characterization of the QoS properties of individual services. It explores the implications of application-level QoS properties in order to select particular services. The proposed characterization presents two dimensions of QoS properties, separating data-related information (functional properties) from physical resources information (non-functional properties). This scheme is proposed and used in the iLAND project where target applications are networked systems for which QoS informaiton is relevant; the execution in these systems must comply with functional and non-functional requirements, especially timing requirements. In this project, the communication middleware performs QoS-based service composition in a time-deterministic manner. To validate the proposed characterization, a service based video application demonstrator is implemented following this scheme, and it shows to be fully compliant with the requirements of the application. It has also proved to be a simple and easy-to-use scheme.

Inspecting overhead cables using autonomous Unmanned Aerial Vehicles (UAVs) is an affordable and promising future solution for providing a clear picture of the energy infrastructure. However, most of today's UAVs for powerline inspection are designed to use the Global Navigation Satellite System (GNSS) to follow the power pylons which compromises the detection accuracy. In this paper, we provide an overview of the current state-of-the-art in sensors that can be used to remotely detect power lines using UAVs. The work compares 20+ low-cost, low-power, and light-weight sensors. The performance of 6 different kinds of sensors is evaluated thoroughly in a real outdoor powerline test setup using a custom UAV. The sensor data is obtained and analyzed using Robot Operating System (ROS) and is provided openly.

It is not feasible to engineer requirements for adaptable and open service-oriented systems (AOSS) by specifying stakeholders’ expectations in detail during system development. Openness and adaptability allow new services to appear at runtime so that ways in, and degrees to which the initial functional and nonfunctional requirements will be satisfied may vary at runtime. To remain relevant after deployment, the initial requirements specification ought to be continually updated to reflect such variation. Depending on the frequency of updates, this paper separates the requirements engineering (RE) of AOSS onto the RE for: individual services (Service RE), service coordination mechanisms (Coordination RE), and quality parameters and constraints guiding service composition (Client RE). To assist existing RE methodologies in dealing with Client RE, the Dynamic Requirements Adaptation Method (DRAM) is proposed. DRAM updates a requirements specification at runtime to reflect change due to adaptability and openness.

There is the resonance phenomenon in the reradiation interference on wireless station from power lines. The wire-surface simulation model, in which steel tower is represented as surface model and ground wire is represented as wire model, is excitated by vertical polarization plane wave. Based on the method of moments (MoM), the base function of wire-surface model junction point and the computation method are discussed. With various frequencies, the interference values are calculated. The possible impact factors of interference resonance, such as ground wire, conductor, number of towers and tower spans, are studied. The results show that the decisive impact factor on reradiation interference is tower spans. It is concluded that interference is mainly decided by electromagnetic scatter from power towers in short wave and above.