Building energy management and data analytics

Zucker, Gerhard; Habib, Usman; Blöchle, Max; Wendt, Alexander; Schaat, Samer; Siafara, Lydia C.

doi:10.1109/sedst.2015.7315253

Cited by 20 publications

(5 citation statements)

References 25 publications

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“…However, these results are on the verge of being implemented in practice, e.g. in the project ECABA 5 [15] in the field of energy management or in the project CogMAS 6 [16] in the field of purchasing predictions.…”

Section: Resultsmentioning

confidence: 99%

The Fourth Outrage of Man (Is the Turing-Test Still up to Date?)

Dietrich¹,

Jakubec²,

Schaat³

et al. 2017

JCP

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This paper addresses psychologists-psychoanalysts in particular-and engineers, as well as others with an interest in technology and a proclivity for critical thinking. We hope to grasp the attention of persons who are skeptical or even uneasy with regard to modern electronic machines. It is important to realize that the mathematician and information theoretician Alan Turing was the first to prompt mankind to consider a comparison between intelligent machines and humans from a scientific perspective. His test proposal piqued the interest of engineers as well as philosophers, and has caused many of them to question their concepts to this day. This treatise aims to show that Turing, a scientist rightfully (albeit belatedly) highly esteemed, formulated a fascinating research question which can be legitimately answered only if one deals intensively and seriously with the disciplines of psychoanalysis and computer engineering. The project SiMA (Simulation of Mental apparatus & Applications) at the Vienna University of Technology assembled a team of scientists who have come to a concise conclusion and formulated an answer to this question. The answer, however, is not what one might expect.

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Section: Resultsmentioning

confidence: 99%

The Fourth Outrage of Man (Is the Turing-Test Still up to Date?)

Dietrich¹,

Jakubec²,

Schaat³

et al. 2017

JCP

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“…They can help to implement countermeasures to increase building resilience and to prevent costly incidents. Zucker et al [145] also reviewed the topics of sensor failure, selection of sensors, processing of sensor data, data analysis of operation data, and data sanitation in building energy system FDD.…”

Section: Summary Of Review Papersmentioning

confidence: 99%

Literature Review for Sensor Impact Evaluation and Verification Use Cases - Building Controls and Fault Detection and Diagnosis (FDD)

Bae

Cui

et al. 2020

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“…Based on the LIDA research [15] and SOAR research [16] mentioned it is also considered in the existence of different types of structures based on prominent agents and architectures in cognitive systems. According to Zucker et al 's research [17] suggested a cognitive architecture is outlined for buildings that use these structures.…”

Section: Cognitive Iot Architecturementioning

confidence: 99%

CIoT-Net: a scalable cognitive IoT based smart city network architecture

Park

Salim

et al. 2019

Hum. Cent. Comput. Inf. Sci.

102

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In the recent era, artificial intelligence (AI) is being used to support numerous solutions for human beings, such as healthcare, autonomous transportation, and so on. Cognitive computing is represented as a next-generation application AI-based solutions which provide human–machine interaction with personalized interactions and services that imitate human behavior. On the other hand, a large volume of data is generated from smart city applications such as healthcare, smart transportation, retail industry, and firefighting. There is always a concern on how to efficiently manage the large volume of generated data. Recently many existing researches discussed the analysis of the large quantity of data using cognitive computing; however, these researches are failed to handle the certain problems, namely scalability, and flexibility of data gathered in a smart city environment. Data captured from millions of sensors can be cross implemented across various cognitive computing applications to ensure real-time responses. In this paper, we study the cognitive internet of things (CIoT) and propose a CIoT-based smart city network (CIoT-Net) architecture which describes how data gathered from smart city applications can be analyzed using cognitive computing and handle the scalability and flexibility problems. We discuss various technologies such as AI and big data analysis to implement the proposed architecture. Finally, we describe the possible research challenges and opportunities while implementing the proposed architecture.

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Building energy management and data analytics

Cited by 20 publications

References 25 publications

The Fourth Outrage of Man (Is the Turing-Test Still up to Date?)

The Fourth Outrage of Man (Is the Turing-Test Still up to Date?)

Literature Review for Sensor Impact Evaluation and Verification Use Cases - Building Controls and Fault Detection and Diagnosis (FDD)

CIoT-Net: a scalable cognitive IoT based smart city network architecture

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