Ambient Intelligence based monitoring and energy efficiency optimisation system

Heilala, Juhani; Klobut, Krzysztof; Salonen, Tapio; Siltanen, Pekka; Ruusu, Reino; Urosevic, Ljubisa; Reimer, Philip; Armijo, Alberto; Sorli, Mikel; Fatur, Tomaz; Gantar, Ziga; Jung, Andreas

doi:10.1109/isam.2011.5942349

Cited by 13 publications

(6 citation statements)

References 2 publications

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“…Envisioning the potentials from computational systems to promote and guarantee sustainability requires all types of sensor classes, as present in some initial project that perform real-time sustainability and energy management [11], [12].…”

Section: A Computational Approach To Sustainabilitymentioning

confidence: 99%

Gamification, Social Networks and Sustainable Environments

Silva¹,

Analide²,

Rosa³

et al. 2013

IJIMAI

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Intelligent environments and ambient intelligence enabled systems provide means to gather rich information from both environments and its users. With the help of such systems, it is possible to foster communities of ambient intelligence systems with community driven knowledge, which is created by individual actions and setups in each of the environments. Such arrangements provides the potential to build systems that promote better practices and more efficient and sustainable environments by promoting the community best examples and engaging users to adopt and develop proactive behaviors to improve their standings in the community. This work aims to use knowledge from communities of intelligent environments to their own benefit. The approach presented in this work uses information from different environments, ranking them according to their sustainability assessment. Recommendations are then computed using similarity and clustering functions ranking users and environments, updating their previous records and launching new recommendations in the process. Gamification concepts are used in order to keep users motivation and engage them actively to produce better results in terms of sustainability

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Section: A Computational Approach To Sustainabilitymentioning

confidence: 99%

Gamification, Social Networks and Sustainable Environments

Silva¹,

Analide²,

Rosa³

et al. 2013

IJIMAI

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“…It is crucial to create adequate awareness of the energy efficiency information, but available system is still lacking. One application of energy efficiency monitoring and optimization system was reported in [13]. Automated monitoring process enables online energy optimization for a process.…”

Section: Literature Reviewmentioning

confidence: 99%

Energy-Efficient Machining via Energy Data Integration

Peng

Heilala

2013

IFIP Advances in Information and Communication Technology

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Abstract. Energy-efficient machining strategies are required to be implemented in daily practice to advance the competitiveness of the enterprises on global scale. Energy information, which currently not considered as an integral part of production data, is studied. A need is identified to integrate energy information into production program and solidify the knowledge for extensive reference. To effectively represent and share the data, standardized format is regarded as one promising approach, thus STEP-NC is adopted. The proposed data models are grouped into four, i.e. automated energy monitoring and recording, energy estimation and labeling, energy optimization, and machine tool energy performance. The developed schema is compliant and harmonized with other parts in STEP-NC standards. A case study is presented to add energy information to STEP-NC file. It can be concluded that standardized data format enables the integration of energy information into the production process and enhances its sustainable performance. Keywords:Energy efficiency, STEP-NC, Data integration, CNC Machining. IntroductionThe world is well-connected and better-informed nowadays than ever before. It is also true to manufacturing domain. New requirements of modern manufacturing industry are placed, such as sustainable performance, minimum supply chain management cost, and optimal product lifecycle performance. Energy-efficient machining system is focused in this study, as it is the key area in metalworking industry for the future. To keep energy efficiently used, energy information from machining process shall be available to assist process planning or lifecycle analysis [1]. A series of simulationbased analysis and decision making systems are developed, focusing on energy usage and performance on product lifecycle level [2]. However, the ways to actually improve the daily practice in factories is still lacking. The separated parties along the production chain desire to seamlessly share energy knowledge and data in a systematic manner. Data representation and exchange activities demand to be universal and consistent. This also contributes to significant savings on supply chain management cost, which is considered as the top priority of the enterprises for the next decade. With the rapid development in CAx, data communication problem exists between different activities, known as "Island of Automation".

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“…[16], process chain simulation considering the production system, the technical business services and the building shell) and at runtime (with ambient information considered together with production system parameter values [17]). The range of EMS services vary in particular implementations, being usually concentrated around long/short term planning and optimisation, on-line monitoring and reporting [15] [17].…”

Section: B Implementation Of Energy Management Systemsmentioning

confidence: 99%

A cross-layer approach to energy management in manufacturing

Florea

Montemayor

Postelnicu

et al. 2012

IEEE 10th International Conference on Industrial Informatics

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Energy management systems (EMS) play an important role to achieve improvements in energy efficiency at manufacturing enterprises. Development and implementation of EMS is rather challenging due to the distributed nature of enterprises and heterogeneity of enterprise medium. Modern ICT solutions and improved architecture paradigms can help to overcome these obstacles. In this paper we propose an energy management system architecture based on SOA 2.0 technologies to ensure intra-and cross-layer interoperability of system components.

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Ambient Intelligence based monitoring and energy efficiency optimisation system

Cited by 13 publications

References 2 publications

Gamification, Social Networks and Sustainable Environments

Gamification, Social Networks and Sustainable Environments

Energy-Efficient Machining via Energy Data Integration

A cross-layer approach to energy management in manufacturing

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