The intelligent fire detection and response system integrates three key components: Fire Type Identification, Fire Tracking, and Dynamic Nozzle control. The Fire Identification component uses a multi-sensor setup (tem...
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The exponential growth of IoT applications due to user demands necessitates the emergence of reliable fog/edge computing systems. Because of the wide-open area of these systems, the tendency for failure in communicati...
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ISBN:
(纸本)9798350372113;9798350372106
The exponential growth of IoT applications due to user demands necessitates the emergence of reliable fog/edge computing systems. Because of the wide-open area of these systems, the tendency for failure in communication channels and computing nodes (resources) is unpredictable, especially in real-time IoT applications. Several studies have aimed at tackling fault and failure issues by employing a variety of resource management strategies. Most studies use heuristics or conventional scheduling approaches that leverage the use of reinforcement learning. The element of reinforcement learning aims to support better governance when resource faults and failures occur. This paper provides an analysis of the implementation of reinforcement learning (RL) into fault-tolerant scheduling in fog/edge computing systems. The efficacy of fault-tolerant scheduling is claimed to be improved through RL with regard to system performance. We grouped the discussion based on three themes: resource failures, reinforcement learning (RL) in general, and RL scheduling for fault tolerance. The discussion could further derive solutions for overcoming the challenges of resource failures in fog/edge systems.
Power line communication (PLC) modems are transmitting high-frequency signals through the electric grid infrastructure. These signals can also be interpreted as probing or sensing signals. PLC is thus a natural candid...
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ISBN:
(数字)9798350318555
ISBN:
(纸本)9798350318562;9798350318555
Power line communication (PLC) modems are transmitting high-frequency signals through the electric grid infrastructure. These signals can also be interpreted as probing or sensing signals. PLC is thus a natural candidate for integrated sensing and communication (ISAC). The implementation of grid sensing or monitoring with PLC has already been studied in previous work. In this paper, we ask the question what accuracy for (fault) parameter estimation can be achieved through power line ISAC. Since this is the first study of this kind, we are mainly concerned with introducing methodology. We adopt the Cramer-Rao lower bound (CRLB) as a performance criterion that is universally applicable regardless of the specific ISAC implementation. We show how to connect measurement variables and unknown parameters typically experienced in grid monitoring to obtain expressions for the CRLB. Using transmissionline modeling for PLC signal propagation, we identify automatic differentiation as a suitable tool to evaluate those expressions. The effectiveness of power line ISAC is illustrated through numerical results for a fault location estimation use case.
This work presents a Fleet Manager for a fleet of Autonomous Mobile Robots (AMRs) that perform material handling tasks in a shared environment. The Fleet Manager assigns AMRs to newly released tasks, computes paths fo...
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ISBN:
(纸本)9798350358513;9798350358520
This work presents a Fleet Manager for a fleet of Autonomous Mobile Robots (AMRs) that perform material handling tasks in a shared environment. The Fleet Manager assigns AMRs to newly released tasks, computes paths for them to travel to the task's locations, and schedules their travel along the computed paths so that conflicts with other AMRs are avoided. The objective is for each AMR to complete its task as quickly as possible, to then be assigned a new task. The Fleet Manager works online, assigning a released task to the AMR closest to the task's location, and then computing the path and schedule to fit in with the already assigned and executing AMRs. Conflicts occur when, in order to reach their targets, AMRs would have to simultaneously occupy the same space. Resolving this is done by appropriate scheduling, or by moving idle AMRs out of the way. For fleet management to be practicable, the computation time for assigning an AMR to a task and computing its path and schedule must be negligible compared to other system times. Tests were conducted to evaluate the performance of the Fleet Manager on a number of benchmark problem instances, counting up to hundreds of AMRs. The results show that the presented Fleet Manager can handle these systems quickly enough to be practically useful in real industrial scenarios.
The global demand for electric vehicles is predicted to grow rapidly. However, charging Electric Vehicles (EVs) presents a challenge for Distribution Networks (DN) utilities. In a smart grid, effective communication b...
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ISBN:
(纸本)9798331517519;9798331517526
The global demand for electric vehicles is predicted to grow rapidly. However, charging Electric Vehicles (EVs) presents a challenge for Distribution Networks (DN) utilities. In a smart grid, effective communication between the charging stations, DN operator, and customers is crucial for arranging multiple charging sessions based on client preferences while following operational grid limits and costs. The modern and smart EV charging stations with interconnectivity requirements and online applications within the smart DN introduce potential risks of cyber-attacks and cause significant technical and financial consequences. Therefore, this study investigates the resilience of a smart distribution grid, specifically integrating EV charging stations and considering different cyber-physical threats. The impact of different cyber-attacks, namely: False Data Injection (FDI) and Man in The Middle (MITM), on low voltage microgrid models including the EV charging stations, are evaluated. The simulation uses a 24-hour load and generation profiles scenario and the results highlight the impact of cyber-physical threats on energy loss, transformer loading and voltage terms.
This paper describes the problem of predicting the occurrence of West Nile Virus (WNV) in mosquitoes in the city of Chicago. Each year, from late May to early October, mosquito traps are set up across the city, and th...
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Emerging energy management systems (EMS) involve devices and services provided by multiple stakeholders. In order to improve the interoperability of these systems, state of the art efforts propose an interoperability ...
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ISBN:
(纸本)9798350381993;9798350382006
Emerging energy management systems (EMS) involve devices and services provided by multiple stakeholders. In order to improve the interoperability of these systems, state of the art efforts propose an interoperability middleware that mediates the communication between end-user applications and EMS components. The potential lack of trust between the different stakeholders raises the need for fine-grained access control mechanisms. However, extending the middleware to support access control in a secure and usable way is a challenging problem. In this paper, we present a solution that achieves fine-grained authorization using Verifiable Credentials (VCs). Our solution leverages VC properties to enable end-users to combine authorizations issued by different entities. Additionally, our solution integrates a cloud-based VC wallet that hides the authorization process from end-user applications, thus facilitating interoperability among EMSes and the development of new, secure applications.
Cleanliness is a very vital aspect of our life, of which household cleaning plays an important role. With the increasing demand for automated cleaning solutions, electronic bots have become an attractive option for ma...
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The image low-pass filter is an effective solution for denoising and improving image quality. The stochastic computing is a novel method for number representation and calculation in stochastic domain. Aiming at the pr...
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