Edge computing is the extension and supplement of cloud computing on the edge of network, and it has a wide application prospect in radio monitoring. In this paper, the advantages of edge computing in radio monitoring...
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The manufacturing of paper is a massive procedure where the effective management of control parameters plays a significant role. These parameters are interrelated with each other and need to be optimized. Several para...
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The agricultural sector is undergoing a transition as automation and robotics converge and evolve. The current labor shortage and the growing need to increase yields are driving innovations in automated agriculture. A...
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The rise and proliferation of Artificial Intelligence (AI) technologies are bringing transformative changes to various sectors, signaling a new era of innovation in fields as diverse as medicine, manufacturing, and ev...
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ISBN:
(纸本)9798350371000;9798350370997
The rise and proliferation of Artificial Intelligence (AI) technologies are bringing transformative changes to various sectors, signaling a new era of innovation in fields as diverse as medicine, manufacturing, and even day-to-day social interactions. Notable advancements are not just confined to textual understanding, as seen in models like GPT, but also extend to visual cognition through image recognition and more. Beyond surface interactions and predictions, AI finds profound applications in life-saving domains such as medical diagnostics and becomes an integral part of daily life through chatbot-based customer interactions. However, as the horizon of AI expands, a crucial yet often overlooked aspect emerges- the underlying mission-critical infrastructure required to support and deploy these models effectively. The intricacies of efficient communication systems, foundational for real-time AI model operations, take center stage in ensuring the seamless functioning of AI-driven applications. This paper explores the quintessential changes needed in communication paradigms to keep pace with the evolving AI landscape. Specifically, we highlight the pivotal role of multipath communication in enhancing the responsiveness and efficiency of AI applications [1]. As a case in point, we investigate its impact on mission-critical operations in robotics. Through experimentation and analysis, the results elucidate the substantial benefits of this approach, revealing a significant improvement in delay metrics. This work underscores the imperative of aligning communication systems with the ever-growing demands of AI, ensuring that infrastructural capabilities do not lag in the race for innovation.
Renewable resources have the potential to address pressing environmental and energy challenges, yet their widespread adoption and utilization in agriculture monitoring remain limited. In particular, remote agricultura...
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With the rapid development of technology, the automotive industry is undergoing unprecedented changes. Among them, the braking system, as an important component of car safety, its technological progress is of great si...
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In Internet-of-Things (IoT) era, integration in multiple levels is needed to effectively address the increasing demands of communication, computation, and sensing (e.g. data acquisition). Federated learning (FL) is wi...
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ISBN:
(纸本)9798350304060;9798350304053
In Internet-of-Things (IoT) era, integration in multiple levels is needed to effectively address the increasing demands of communication, computation, and sensing (e.g. data acquisition). Federated learning (FL) is widely regarded as a promising distributed machine learning framework to enable network intelligence in future-generation networks. Using over-the-air computation (AirComp) (already as an integration of communication and computation) for spectral-efficient FL model aggregation requires massive devices to transmit over the same orthogonal resources. For further integration gain, it is considered employing the same signal for coordinated device joint target sensing, which constitutes a fully integrated scenario of sensing, computing and communication (ISCC). This work focuses on the client selection and power control problem as crucial challenges of AirComp-FL in such scenarios while a requirement of a sensing task as target detection needs to be satisfied. A flexible system design has been proposed by allowing three groups of clients to be chosen: those participating in communication and communication, those solely for sensing, and the ones that transmit nothing. This work proposes a polynomial-time complexity algorithm. Simulation results corroborate the importance and the performance of the proposed framework.
Cloud computing has transformed the digital landscape, providing scalability, cost efficiency, and seamless access to computing resources. Yet, there is a gap between its theoretical aspirations and real-world achieve...
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With increasing numbers of mobile robots arriving in real-world applications, more robots coexist in the same space, interact, and possibly collaborate. Methods to provide such systems with system size scalability are...
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ISBN:
(纸本)9798350384581;9798350384574
With increasing numbers of mobile robots arriving in real-world applications, more robots coexist in the same space, interact, and possibly collaborate. Methods to provide such systems with system size scalability are known, for example, from swarm robotics. Example strategies are self-organizing behavior, a strict decentralized approach, and limiting the robot-robot communication. Despite applying such strategies, any multi-robot system breaks above a certain critical system size (i.e., number of robots) as too many robots share a resource (e.g., space, communication channel). We provide additional evidence based on simulations, that at these critical system sizes, the system performance separates into two phases: nearly optimal and minimal performance. We speculate that in real-world applications that are configured for optimal system size, the supposedly high-performing system may actually live on borrowed time as it is on a transient to breakdown. We provide two modeling options (based on queueing theory and a population model) that may help to support this reasoning.
The traditional industrial communication system can't meet the increasing demands of low delay, high reliability and accurate time synchronization. Time-Sensitive Networking (TSN) technology, with its unique timin...
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