this paper introduces a novel embedded edge computing system for the Internet of things, specifically designed for predictive maintenance of grinding motors in Aerobic Digesters with Liquid Outputs. Low-power sensors ...
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ISBN:
(纸本)9798350385434;9798350385427
this paper introduces a novel embedded edge computing system for the Internet of things, specifically designed for predictive maintenance of grinding motors in Aerobic Digesters with Liquid Outputs. Low-power sensors and Machine Learning algorithms are integrated, using vibration and sound data for real-time monitoring and proactive anomaly detection. through the evaluation of the proposed system in real-life environments, an improved performance compared to state-of-the-art models is demonstrated, emphasizing its potential for enhancing the reliability and efficiency of resource utilization in food waste management practices.
In response to the increasing complexity of real-timeembedded software, driven by the need for intelligent computation in constrained environments, multicore architectures have emerged as a promising solution. the ch...
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ISBN:
(纸本)9798350387964;9798350387957
In response to the increasing complexity of real-timeembedded software, driven by the need for intelligent computation in constrained environments, multicore architectures have emerged as a promising solution. the challenge lies in to choose an effective mapping of the real-time tasks to the various computational resources of these embedded boards, while ensuring real-time constraint satisfaction. To address this problem, our approach rests on two pillars. the first is a domain-specific language designed to capture hardware and software characteristics, constraints, and criteria in a clear and unambiguous manner. the second is a solver method based on Satisfiability Modulo theories solver augmented with a lazy theory to handle real-time aspects. this method allows us to synthesize mappings that respect temporal constraints and optimize specific criteria, such as the power consumption of the embedded board.
the Robotic Mobile Fulfillment System (RMFS) is an automated technology to fulfill various types of orders (e.g.,vehicle assembly) in modern warehouses or factories. In particular, battery-equipped mobile robots move ...
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ISBN:
(纸本)9798350387964;9798350387957
the Robotic Mobile Fulfillment System (RMFS) is an automated technology to fulfill various types of orders (e.g.,vehicle assembly) in modern warehouses or factories. In particular, battery-equipped mobile robots move racks that contain various components (Stock Keeping Unit) by visiting replenishment or picking stations to complete orders. We formulate the preliminary system model to optimize the order throughput and energy consumption of mobile robots, which consists of (i) rack allocation, (ii) task allocation, and (iii) route routing.
Standard distribution middleware has traditionally been perceived as complex software which is not suitable for satisfying the highest certification criteria in safety-critical environments. However, this idea is slow...
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ISBN:
(纸本)9798350387964;9798350387957
Standard distribution middleware has traditionally been perceived as complex software which is not suitable for satisfying the highest certification criteria in safety-critical environments. However, this idea is slowly changing and there are efforts such as the Future Airborne Capability Environment (FACE) consortium to integrate standard distribution middleware into the development of avionic systems. this integration facilitates the interoperability and portability of avionic applications, but there are still challenges that need to be addressed before full success can be achieved. To this end, this paper explores the usage of the Data Distribution Service for real-timesystems (DDS) on top of a partitioned system with a communication network based on the ARINC 664 specification (precisely, the AFDX network). this work specifically identifies the incompatibilities between the two standards and also proposes potential solutions. A set of overhead metrics of using DDS in a distributed partitioned platform is also provided.
Cache locking is a commonly used mechanism to improve both performance and predictability for embedded programs. Dynamic cache locking methods proposed in the literature, where the locked content is modified during ex...
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ISBN:
(纸本)9798350387964;9798350387957
Cache locking is a commonly used mechanism to improve both performance and predictability for embedded programs. Dynamic cache locking methods proposed in the literature, where the locked content is modified during execution, require inserting locking and unlocking instructions in the program's code. In this paper, we introduce a novel hardware mechanism that leverages the LRU age bits to perform duration-based locking. Our proposed mechanism dynamically locks and unlocks cache lines for different durations at run-time, without the need to modify the program's code. We further devise a heuristic that analyzes a program's loop structure and selects the set of addresses to be locked in a L1 instruction cache alongside their locking durations. Evaluation results show that our duration-based locking mechanism achieves comparable results to the dynamic approach while substantially reducing the initialization overhead and avoiding program code modifications.
Machine learning has attracted a lot of interest in the last few years as a solution to a variety of difficult challenges in many disciplines. An emerging area is that of embedded devices, where machine learning is de...
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ISBN:
(纸本)9798350332865
Machine learning has attracted a lot of interest in the last few years as a solution to a variety of difficult challenges in many disciplines. An emerging area is that of embedded devices, where machine learning is deployed to efficiently carry out tasks like data analysis, prediction, and decision-making in real-timeapplications. Challenges such as the necessity for fast and effective algorithms and the restricted resources available in embeddedsystems to cover the computational and storage demands need to be confronted to successfully integrate machine learning models into embeddedsystems. this work aims to provide an overview of the use of machine learning in embeddedsystems, including past and current solutions, and to present the challenges that need to be addressed. Future directions for the use of machine learning in embeddedsystems are also discussed.
Mobile Edge computing (MEC) places computing and storage resources on the network's edge, which opens the door for implementing an entirely new set of delay-sensitive and compute-intensive applications in constrai...
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ISBN:
(纸本)9798350366457;9798350366440
Mobile Edge computing (MEC) places computing and storage resources on the network's edge, which opens the door for implementing an entirely new set of delay-sensitive and compute-intensive applications in constrained IoT devices. Nevertheless, from the perspective of an IoT device, using MEC introduces several challenges that need to be addressed. One is the proper execution and resource utilization of device-native and edge-dependent tasks, especially when considering multi-task edge applications. Current real-time schedulers do not contemplate factors inherent to the nature of MEC, such as shared resource utilization, dynamic execution site migrations, the influence of remote computing, etc. therefore, this paper introduces an agent embedded in IoT devices to provide real-time schedulers with mobile edge computing awareness. Moreover, the performance of the proposed solution is assessed by running two multi-task edge applications in the smart vehicles domain, depicting a considerable task throughput enhancement when compared to existing real-time schedulers.
the proceedings contain 114 papers. the topics discussed include: application of artificial neural networks for processing some biomedical data;distinguishing between AI images and real images with hybrid image classi...
ISBN:
(纸本)9798350387568
the proceedings contain 114 papers. the topics discussed include: application of artificial neural networks for processing some biomedical data;distinguishing between AI images and real images with hybrid image classification methods;securing Durres Port's digital transformation: cybersecurity strategy for maritime industry;linguistic encryption for underwater communication;a toolset for blood pressure visualization and measurement in time, frequency and time-frequency domains;using a shape from polarization to determine the 3D surface of objects withthermal radiation;on the influence of cell libraries and other parameters to SCA resistance of crypto IP cores;integration of PXROS-HR with micro-ROS in robotic systems;and traffic-aware video streaming topology reconfiguration for smart city applications.
As autonomous driving systems mature, the importance of fault tolerance to provide safe operation even in hazardous conditions becomes a key issue in deployment. In an autonomous driving system composed of redundant d...
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ISBN:
(纸本)9798350387964;9798350387957
As autonomous driving systems mature, the importance of fault tolerance to provide safe operation even in hazardous conditions becomes a key issue in deployment. In an autonomous driving system composed of redundant devices, it is necessary to maintain consistency across the system regarding which devices should currently be handling processing. In this paper, we present a new leader election algorithm for autonomous driving systemsthat guarantees consistency in the presence of the failure of any single system component. To make the algorithm practical for autonomous driving systems, we design it to both handle network link failures and guarantee liveness in the presence of a single failure. Due to the safety-critical nature of our environment and the known difficulty of testing distributed algorithms, we use formal verification to validate our proposed algorithm. Our experiments show that the algorithm completes with reasonable time in a simulated environment of an autonomous driving system.
Model-based systems engineering (MBSE) is a methodology that entails creating and utilizing models across the entire system development lifecycle. Based on the Unified Modeling Language (UML), systems Modeling Languag...
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ISBN:
(纸本)9798350387568;9798350387575
Model-based systems engineering (MBSE) is a methodology that entails creating and utilizing models across the entire system development lifecycle. Based on the Unified Modeling Language (UML), systems Modeling Language (SysML) is developed to facilitate intricate industrial systems' behavioral description and design. Open computing Language (OpenCL) has emerged as a pivotal tool for conceptualizing intricate device functionalities. It has been introduced into FPGA design to overcome the inefficiencies of traditional HDL design methodologies and the inability of design methodologies using High-level behavioral description in C/C++ to design the circuits. the study aims to streamline the transformation process from high-level SysML specifications to executable OpenCL code, thereby facilitating the implementation of complex systems. the paper introduces a data pipelining and a task parallelism approach for mapping high-level SysML specifications onto an OpenCL platform model. A detailed case study is presented to demonstrate the effectiveness of the proposed approach in the context of a real-timethree-dimensional particle tracking velocimetry (3D PTV) system. the proposed parallel programming approach converts the comprehensive SysML model of the PTV system into executable OpenCL code. this research applies to multiple applications using the open-source modeling and formal verification tool TTool.
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