Object lessons learned from a distributed system for remote building monitoring and operation

Olken, Frank; Jacobsen, Hans‐Arno; McParland, Chuck; Piette, Mary Ann; Anderson, Mary F.

doi:10.1145/286936.286968

Cited by 4 publications

(7 citation statements)

References 6 publications

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“…In order to avoid anomalies due to inconsistent time formats (e.g because of different time zones), we adopted the convention of storing all timestamps using UTC (Universal Coordinated Time) format. This, further discussed in [3], is a common practice in DASs.…”

Section: Observationsmentioning

confidence: 98%

“…A phenomenon type defines the units on which observations of this phenomenon type are expressed. We adopt the convention of using standard SI (metric) units, as proposed in [3], for phenomenon types. Eventually, a phenomenon type records the set of potential qualitative values that a measurement of such phenomenon type can take (e.g.…”

Section: Device Modelsmentioning

confidence: 99%

“…Remote access to this information provides significant benefits by allowing for the collection of condition-related data from wherever equipment is located. Remote monitoring systems exist in different business areas such as building [3], power engineering [4] and transportation systems [5]. Some remote monitoring systems make use of the Internet network and Internet technologies.…”

Section: Introductionmentioning

confidence: 99%

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A Conceptual Model for Remote Data Acquisition Systems

Nieva

Wegmann

2000

Conceptual Modeling — ER 2000

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Abstract. Data acquisition systems (DAS) are the basis for building monitoring tools that enable supervision of local and remote systems. Unfortunately, DASs are commonly based on proprietary technologies. The data format usually depends on the industrial process, the fieldbus characteristics or the development platform. Currently, there are many standards of DASs, but none of them offer a well-accepted Application Programming Interface (API). However, all of them comply with the same conceptual model. Understanding this model allows for the significant improvement of the design of a specific DAS. In this paper, we propose a conceptual model of a generic DAS. This model gives researchers an abstraction of DASs and a quasi-formal specification of a generic DAS. It also enables developers to compare the existing standards and/or to propose a new open standard.

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Section: Observationsmentioning

confidence: 98%

Section: Device Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Conceptual Model for Remote Data Acquisition Systems

Nieva

Wegmann

2000

Conceptual Modeling — ER 2000

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“…To apply condition monitoring, the access to utility data source is essential. Remote monitoring systems have been developed in many business areas such as building (e.g., Olken et al, 1998), power engineering (e.g., Itschner et al, 1998) and transportation systems (e.g., Fabri et al, 1999) to provide conditionmonitoring systems with information about the state of equipment. The kernel of any remote monitoring system is a data acquisition system (DAS), which enables the collection of relevant data.…”

Section: /22mentioning

confidence: 99%

A conceptual model for remote data acquisition systems

Nieva

Wegmann

2002

Computers in Industry

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Abstract. Data Acquisition Systems (DAS) are the basis for building monitoring tools that enable the supervision of local and remote systems. DASs are complex systems. It is difficult for developers to compare proprietary generic DAS products and/or standards, and the design of a specific DAS is costly. In this paper we propose a conceptual model of a generic DAS. This model gives DAS developers an abstraction of DASs; it enables them to compare existing products and standards; and it provides the DAS developers that aim to develop a specific DAS with a starting point for the design of a specific DAS. We have found that a conceptual model of a generic system has many advantages. We propose patterns and techniques that are useful for the development of conceptual models of generic systems.

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“…calls for means to monitor and control the embedded system without the need to be physically at the place of the observed system. We will follow a remote monitoring approach using Internet technologies as it is used in applications in the automation domain [1,2,3,4] and in railway transportation systems [5].…”

Section: Introductionmentioning

confidence: 99%

Remote Target Monitoring in Embedded Systems Lab Courses using a Sensor Network

Trodhandl

Proske

Elmenreich

2006

IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics

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-This paper describes an architecture for remote monitoring of a distributed embedded system via Internet. The data at the target system is gathered with a time-triggered sensor network which transmits the measured values to a local target server. The sensor network approach makes the system easily adaptable to different embedded target systems.The sensor network is connected to a target server that communicates via Internet with visualization and programming tools at the monitoring computer. The visualization clients provide a live display of the parameters of the observed system.The target server acts as a gateway between target system and monitoring clients and provides security and authentication features for connecting monitoring clients. One target server is able to serve for multiple target systems.As a case study, the presented system will be used in an embedded systems lab course where students are requested to implement various applications on an embedded target board. Using the remote monitoring feature, a student is able to do the work from his or her home place.

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Object lessons learned from a distributed system for remote building monitoring and operation

Cited by 4 publications

References 6 publications

A Conceptual Model for Remote Data Acquisition Systems

A Conceptual Model for Remote Data Acquisition Systems

A conceptual model for remote data acquisition systems

Remote Target Monitoring in Embedded Systems Lab Courses using a Sensor Network

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