Competences as Services in the Autonomic Cycles of Learning Analytic Tasks for a Smart Classroom

González-Eras, Alexandra; Buendía, Omar; Aguilar, José; Cordero, Jorge; Rodriguez, Taniana

doi:10.1007/978-3-319-67283-0_16

Cited by 6 publications

(6 citation statements)

References 24 publications

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“…The work brings data-based ACODAT concept from other fields and applies it to a multi-HVAC model, for the building HVAC management. The ACODAT concept was successfully proven in telecommunications [6], Education with smart classroom [7,8], but it is still unknown in HVAC management [1].…”

Section: Discussionmentioning

confidence: 99%

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An Autonomic Cycle of Data Analysis Tasks for the Supervision of HVAC Systems of Smart Building

Aguilar¹,

Ardila²,

Avendaño³

et al. 2020

Energies

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Early fault detection and diagnosis in heating, ventilation and air conditioning (HVAC) systems may reduce the damage of equipment, improving the reliability and safety of smart buildings, generating social and economic benefits. Data models for fault detection and diagnosis are increasingly used for extracting knowledge in the supervisory tasks. This article proposes an autonomic cycle of data analysis tasks (ACODAT) for the supervision of the building’s HVAC systems. Data analysis tasks incorporate data mining models for extracting knowledge from the system monitoring, analyzing abnormal situations and automatically identifying and taking corrective actions. This article shows a case study of a real building’s HVAC system, for the supervision with our ACODAT, where the HVAC subsystems have been installed over the years, providing a good example of a heterogeneous facility. The proposed supervisory functionality of the HVAC system is capable of detecting deviations, such as faults or gradual increment of energy consumption in similar working conditions. The case study shows this capability of the supervisory autonomic cycle, usually a key objective for smart buildings.

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Section: Discussionmentioning

confidence: 99%

“…ACODAT is decision-making oriented [5,7,8], and its tasks work together to achieve the objective of the supervised process. The tasks have different roles in the autonomous cycle, such as observing the process, analyzing and interpreting the events and making decisions to reach the objective for which the cycle was designed.…”

Section: Self-managementmentioning

confidence: 99%

An Autonomic Cycle of Data Analysis Tasks for the Supervision of HVAC Systems of Smart Building

Aguilar¹,

Ardila²,

Avendaño³

et al. 2020

Energies

Self Cite

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“…This is why the concept of "Autonomic Cycles of Data Analytics Tasks" is developed for each strategic objective of a studied process. Thus, in [3,11], ACODAT is defined as a set of data analysis tasks whose purpose is to improve the process under study. This set of tasks interact among them, performing different roles: (1) process observers, (2) situation and event analyzers and interpreters, and (3) decision-makers to improve it (see Figure 1).…”

Section: A Autonomic Cycles Of Data Analysis Tasksmentioning

confidence: 99%

“… Decision-making Tasks: They define the actions to be carried out in order to improve the process, considering the objectives defined for the autonomous cycle. ACODAT paradigm was initially proposed for smart classrooms [3,11] and later applied to different fields, such as Telecommunications [19] or Industry 4.0 [17,24,25].…”

Section: Figure 1 Autonomous Cycle Of Data Analysis Tasksmentioning

confidence: 99%

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Autonomic Management of a Building’s Multi-HVAC System Start-Up

et al. 2021

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Most of the studies about control, automation, optimization and supervision of building HVAC systems are about the steady-state regime, i.e. when the equipment is already working on their setpoints. In this work, it is defined an approach for multi-HVAC systems to reach the setpoint at the startup, so that other steady statebased strategies can smoothly come into operation to control and supervise their operations. The proposed approach for the management of the transient regime for multi-HVAC systems is based on the "Autonomic Cycle of Data Analysis Tasks" concept. In this case, it is composed of two data analysis tasks: one for determining if the system is going towards the defined operational setpoint, and if it was not the case, another for reconfiguring the operational mode of the multi-HVAC system to redirect it. The proposal is proved in a real context that characterizes one multi-HVAC system and its operational setpoints. The performance obtained from the experiments in diverse situations is encouraging, since they show how this approach leads the multi-HVAC system to reach the setpoint optimizing contradictory objectives, such as to attain the desired comfort, or reduce the energy costs, among others.

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Determination of Professional Competencies Using an Alignment Algorithm of Academic Profiles and Job Advertisements, Based on Competence Thesauri and Similarity Measures

González-Eras

Aguilar

2019

Int J Artif Intell Educ

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Competences as Services in the Autonomic Cycles of Learning Analytic Tasks for a Smart Classroom

Cited by 6 publications

References 24 publications

An Autonomic Cycle of Data Analysis Tasks for the Supervision of HVAC Systems of Smart Building

An Autonomic Cycle of Data Analysis Tasks for the Supervision of HVAC Systems of Smart Building

Autonomic Management of a Building’s Multi-HVAC System Start-Up

Determination of Professional Competencies Using an Alignment Algorithm of Academic Profiles and Job Advertisements, Based on Competence Thesauri and Similarity Measures

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