14 results on '"Micro-moments"'
Search Results
2. Multi-sensor data fusion framework for energy optimization in smart homes.
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Dasappa, Nirupam Sannagowdara, Kumar G, Krishna, and Somu, Nivethitha
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DEEP learning , *SMART homes , *MULTISENSOR data fusion , *MACHINE learning , *ENERGY development , *COMPUTING platforms - Abstract
Advancements in Internet of Energy (IoE) technologies drive the development of several energy efficient frameworks for better energy optimization, economic savings, safety, and security in smart homes. However, certain challenges such as real-time operational data for each micro-moment, proper application of data fusion techniques, and end-to-end computing and deployment architecture prevent the establishment of an effective energy-efficient framework to provide personalized energy-saving recommendations. This work presents energy management for smart spaces (EMSS), the proposed energy efficiency framework implemented in an edge-cloud computing platform that fuses data from heterogeneous data sources (environmental sensors, camera, plug data, etc.) at appropriate data fusion levels and process them to generate actionable, explainable, personalized, and persuasive recommendations at the right moment. The user response to the generated recommendations triggers the actuators to perform respective energy-saving actions and provide more personalized future recommendations. Further, SMARTHome - a data generation framework based on configurable scenario files and a set of software codes was proposed to generate synthetic data with respect to different building types and micro-moments. The functionalities of the EMSS (device and user registration), user dashboard, analytics, and energy-saving recommendations were made accessible to the user through web and mobile applications. The validation analysis of the EMSS was performed by (i) comparative analysis of the machine learning and deep learning algorithms used by the decision engine to generate energy-saving recommendations and (ii) benchmarking of EMSS based on the taxonomy of data fusion-based energy efficiency frameworks for smart homes. [Display omitted] • EMSS, an end-to-end energy efficiency framework for smart spaces. • SMARTHome, data generation framework to generate synthetic dataset. • Smart data fusion approach to apply different levels of data fusion. • Actionable, explainable, persuasive, and personalized energy-saving recommendations. • Implemented on an edge-cloud computing platform. [ABSTRACT FROM AUTHOR] more...
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- 2024
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3. A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks.
- Author
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Himeur, Yassine, Alsalemi, Abdullah, Bensaali, Faycal, and Amira, Abbes
- Abstract
Nowadays, analyzing, detecting, and visualizing abnormal power consumption behavior of householders are among the principal challenges in identifying ways to reduce power consumption. This paper introduces a new solution to detect energy consumption anomalies based on extracting micro-moment features using a rule-based model. The latter is used to draw out load characteristics using daily intent-driven moments of user consumption actions. Besides micro-moment features extraction, we also experiment with a deep neural network architecture for efficient abnormality detection and classification. In the following, a novel anomaly visualization technique is introduced that is based on a scatter representation of the micro-moment classes, and hence providing consumers an easy solution to understand their abnormal behavior. Moreover, in order to validate the proposed system, a new energy consumption dataset at appliance level is also designed through a measurement campaign carried out at Qatar University Energy Lab, namely, Qatar University dataset. Experimental results on simulated and real datasets collected at two regions, which have extremely different climate conditions, confirm that the proposed deep micro-moment architecture outperforms other machine learning algorithms and can effectively detect anomalous patterns. For example, 99.58% accuracy and 97.85% F1 score have been achieved under Qatar University dataset. These promising results establish the efficacy of the proposed deep micro-moment solution for detecting abnormal energy consumption, promoting energy efficiency behaviors, and reducing wasted energy. [ABSTRACT FROM AUTHOR] more...
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- 2020
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4. The Emergence of Hybrid Edge-Cloud Computing for Energy Efficiency in Buildings
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Abdullah Alsalemi, Abbes Amira, Faycal Bensaali, and Yassine Himeur
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Computer science ,business.industry ,Energy efficiency in buildings ,Distributed computing ,Cloud computing ,Deep learning ,Energy consumption ,Edge computing ,Micro-moments ,Power (physics) ,Hybrid edge-cloud computing ,Anomaly detection ,Enhanced Data Rates for GSM Evolution ,business ,Energy (signal processing) ,Efficient energy use - Abstract
Edge computing is attracting an increasing attention presently even though most of the building energy efficiency solutions are still using cloud computing for gathering, pre-processing and analyzing energy data. However, edge computing still requires more power in order to be used alone to meet the high computation demand of artificial intelligence based energy saving solutions. Meanwhile, a hybrid edge-cloud architecture can be the best current approach to implement energy efficiency systems. It provides end-users and utility companies with a flexible control of their energy usage footprints, minimizes the cost of cloud hosting, and improves privacy-preservation. Accordingly, in this paper, we present a novel energy efficiency system based on a hybrid edge-cloud computing architecture. To analyze energy and occupancy data collected through different smart meters and occupancy sensors, we use a micro-moment approach to cluster energy observations into different categories representing both normal and abnormal energy usage. Following, a deep micro-moments (deepM2) scheme is deployed to automate the Anomaly Detection task, where a new approach called deepM2-AD is developed. Moving forward, deepM2-AD is implemented on three different architectures, defined as edge-only, cloud-only and hybrid edge-cloud to evaluate their performance and identify their merits and demerits. Overall, the hybrid edge-cloud architecture has presented the best compromise in terms of improving the processing speed, curtailing the cost of cloud hosting, and reducing the communication latency. Therefore, it has a great potential for supporting real-time energy consumption anomaly detection applications that help in minimizing wasted energy. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. Acknowledgments. This paper was made possible by National Priorities Research Program (NPRP) grant No. 10-0130-170288 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Scopus more...
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- 2022
5. Detection of Appliance-Level Abnormal Energy Consumption in Buildings Using Autoencoders and Micro-moments
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Yassine Himeur, Abdullah Alsalemi, Faycal Bensaali, and Abbes Amira
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Excessive consumption ,Consumption while outside ,Appliance-level energy consumption ,Anomaly detection ,Autoencoder ,Micro-moments - Abstract
The detection of anomalous energy usage could help significantly in signaling energy wastage and identifying faulty appliances, especially if the individual power traces are analyzed. To that end, this paper proposes a novel abnormal energy consumption detection approach at the appliance-level using autoencoder and micro-moments. Accordingly, energy usage footprints of different household appliances along with occupancy patterns are analyzed for modeling normal energy consumption behaviors, and on the flip side, detecting abnormal usage. In effect, energy micro-moments occur when end-users reflexively (i) switch on/off an appliance to start/stop an energy consumption action; (ii) increase/reduce energy consumption of a specific appliance; and (iii) enter/leave a specific room. Put differently, energy micro-moments are captured by reference to end-users' daily tasks usually performed to meet their preferences. In this regard, energy micro-moment patterns are extracted from appliance-level consumption fingerprints and occupancy data using an innovative rule-based algorithm to represent the key intent-driven moments of daily energy use, and hence model normal and abnormal behaviors. Moving forward, energy micro-moment patterns are fed into an autoencoder including 48 input/output neurons, and 4 neurons in the intermediate layer aiming at reducing the computational cost and improving the detection performance. This has helped in accurately detecting two kinds of anomalous energy consumption, i.e. "excessive consumption" and "consumption while outside", where up to 0.95 accuracy and F1 score have been achieved, for example, when analyzing microwave energy consumption. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. Acknowledgements. This paper was made possible by National Priorities Research Program (NPRP) grant No. 10-0130-170288 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Scopus more...
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- 2022
6. The Janus Dialectic of Corporate Social Irresponsibility and Corporate Social Responsibility – The Role of Micro-Moments
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Stokes, Peter
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- 2012
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7. Elevating Energy Data Analysis with M2GAF: Micro-Moment Driven Gramian Angular Field Visualizations
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Alsalemi, Abdullah, Amira, Abbes, Malekmohamadi, Hossein, Diao, Kegong, and Bensaali, Faycal
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Gramian angular fields ,data visualization ,internet of energy ,artificial intelligence ,micro-moments ,energy efficiency - Abstract
open access proceedings With global pollution and buildings power consumption on the rise, energy efficiency research has never been more necessary. Accordingly, data visualization is one of the most sought challenges in data analysis, especially in energy efficiency applications. In this paper, a novel micro-moment Gramian angular fields time-series transformation of energy signals and ambient conditions, abbreviated as M2 GAF, is described. The proposed tool can be used by energy efficiency researchers to yield a deeper understanding of building energy consumption data and its environmental conditions. Current results show sample G2 GAF representation for three power consumption datasets. In summary, the proposed tool can unveil novel energy time-series analysis possibilities as well as original data visualization that can yield deeper insights, and in turn, improved energy efficiency. more...
- Published
- 2021
8. Appliance-Level Monitoring with Micro-Moment Smart Plugs
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Abbes Amira, Abdullah Alsalemi, Faycal Bensaali, and Yassine Himeur
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,education.field_of_study ,Internet of things ,Computer Science - Artificial Intelligence ,business.industry ,Computer science ,Population ,Real-time computing ,Energy consumption ,Micro-moments ,Unit (housing) ,Machine Learning (cs.LG) ,Domestic energy usage ,Artificial Intelligence (cs.AI) ,Energy efficiency ,Software deployment ,Home automation ,Environmental monitoring ,Recommender systems ,Wireless ,business ,education ,Smart plug ,Efficient energy use - Abstract
Human population are striving against energy-related issues that not only affects society and the development of the world, but also causes global warming. A variety of broad approaches have been developed by both industry and the research community. However, there is an ever increasing need for comprehensive, end-to-end solutions aimed at transforming human behavior rather than device metrics and benchmarks. In this paper, a micro-moment-based smart plug system is proposed as part of a larger multi-appliance energy efficiency program. The smart plug, which includes two sub-units: the power consumption unit and environmental monitoring unit collect energy consumption of appliances along with contextual information, such as temperature, humidity, luminosity and room occupancy respectively. The plug also allows home automation capability. With the accompanying mobile application, end-users can visualize energy consumption data along with ambient environmental information. Current implementation results show that the proposed system delivers cost-effective deployment while maintaining adequate computation and wireless performance., Comment: This paper has been accepted in SCA2020: The Fifth international conference on Smart City Applications more...
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- 2021
9. Micro-moments, choice and responsibility in sustainable organizational change and transformationThe Janus dialectic.
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Stokes, Peter and Harris, Phil
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ETHICS ,VIRTUE ,CHANGE management ,SOCIAL responsibility ,SUSTAINABLE development - Abstract
Purpose – This paper's aim is to examine the catalytic and pivotal role of micro-moments in organizations and their role in producing the possibility of sustainable or unsustainable change and transformation. Design/methodology/approach – The paper employs participant observation within an interpretivistic methodological approach. This provides critical incident vignettes with which to explore issues. Findings – The argument contends that macro-events in relation to either (un)sustainable and (ir)responsible events are rooted in "micro-moments" centred on behaviour and choices. These myriad choices occur repeatedly – a dilemma captured by the metaphor of Janus. Underpinned by templates of Aristotelian virtue ethics and Kantian deontology, the paper argues that consistent "good" character" and "good behaviour" are central to ensuring sustainable change. Alternatively, "bad" character and behaviours have a propensity to engender ambivalent unsustainable and irresponsible environments. Social implications – The work heightens awareness of seemingly "insignificant" micro-behaviour in organizations undergoing processes of change. If allowed to occur without redress, negative micro-moments lead to negative impacts on the macro-aspects of the organization whereas positive moments tend to engender more sustainable and responsible environments. Originality/value – The paper builds an amalgam of extant literatures on business ethics, organizational behaviour, corporate culture, organizational change management and sustainability and focuses attention on the under-developed phenomenon of the micro-moment. [ABSTRACT FROM AUTHOR] more...
- Published
- 2012
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10. The Micro-Dynamics of Intraorganizational and Individual Behavior and Their Role in Organizational Ambidexterity Boundaries.
- Author
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Stokes, Peter, Moore, Neil, Moss, Danny, Mathews, Martin, Smith, Simon M., and Liu, Yipeng
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CORPORATE culture ,FIELDWORK (Educational method) ,MOTOR ability ,ETHNOLOGY research ,CHANGE management - Abstract
Organizational ambidexterity has emerged as a valuable contemporary lens on organizational design and action, examining the dynamic relationships between exploitative (extant) and explorative (evolving) resources within organizational contexts and environments. This article analyzes the literature pertaining to ambidexterity and underlines a number of recurrent preoccupations including definition of the nature, characteristics, and normative boundaries of organizational ambidexterity; a predilection toward considering interfirm/unit comparisons of large-scale corporate organizations; and a concentration on the significance of the managerialistic role of the senior management team's disposition and action-orientations. While a few calls have been made for a focus on the micro-aspects, predominant attention has remained on the macro-aspects of organizational ambidexterity. The aim of the article, therefore, is to conduct a complementary study that considers the boundaries and transitions between exploitative and explorative modes at the intraorganizational, individual micro-behavioral level. To facilitate this, the article surfaces and underscores the paradigmatic modernistic characterization of large areas of the current organizational ambidexterity literature and the implications of this. Moreover, it explores alternative potentially useful critical paradigms that assist in providing tools with which to examine the 'micro.' The research conducts an ethnographic-style study of a quasi-public training and development organization to illustrate the above background contexts and the micro-interface and boundary of explorative and exploitative modes of organizational ambidexterity in the intraorganizational situation. Within this, the study points up the significance of the role of sense-making in operational micro-moment individual and small-group situations, and their vital influence in ultimately underpinning, and contributing to, macro-organizational ambidextrous contexts. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR] more...
- Published
- 2015
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11. Building power consumption datasets: Survey, taxonomy and future directions.
- Author
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Himeur, Yassine, Alsalemi, Abdullah, Bensaali, Faycal, and Amira, Abbes
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ENERGY consumption of buildings , *DATA collection platforms , *RECOMMENDER systems , *ANOMALY detection (Computer security) , *ENERGY consumption - Abstract
• Review of building power consumption datasets. • Data collection platforms. • Power consumption anomaly detection dataset. • Improving datasets collection and exploitation. • Visualization of power consumption micro-moments. In the last decade, extended efforts have been poured into energy efficiency. Several energy consumption datasets were henceforth published, with each dataset varying in properties, uses and limitations. For instance, building energy consumption patterns are sourced from several sources, including ambient conditions, user occupancy, weather conditions and consumer preferences. Thus, a proper understanding of the available datasets will result in a strong basis for improving energy efficiency. Starting from the necessity of a comprehensive review of existing databases, this work is proposed to survey, study and visualize the numerical and methodological nature of building energy consumption datasets. A total of thirty-one databases are examined and compared in terms of several features, such as the geographical location, period of collection, number of monitored households, sampling rate of collected data, number of sub-metered appliances, extracted features and release date. Furthermore, data collection platforms and related modules for data transmission, data storage and privacy concerns used in different datasets are also analyzed and compared. Based on the analytical study, a novel dataset has been presented, namely Qatar university dataset, which is an annotated power consumption anomaly detection dataset. The latter will be very useful for testing and training anomaly detection algorithms, and hence reducing wasted energy. Moving forward, a set of recommendations is derived to improve datasets collection, such as the adoption of multi-modal data collection, smart Internet of things data collection, low-cost hardware platforms and privacy and security mechanisms. In addition, future directions to improve datasets exploitation and utilization are identified, including the use of novel machine learning solutions, innovative visualization tools and explainable mobile recommender systems. Accordingly, a novel visualization strategy based on using power consumption micro-moments has been presented along with an example of deploying machine learning algorithms to classify the micro-moment classes and identify anomalous power usage. [ABSTRACT FROM AUTHOR] more...
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- 2020
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12. MICRO-MOMENTS OF USER EXPERIENCE: AN APPROACH TO UNDERSTANDING ONLINE USER INTENTIONS AND BEHAVIOR
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Antun Biloš, Davorin Turkalj, Ivan Kelić, Dobrinić, Damir, and Gregurec, Iva
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micro-moments ,mobile devices ,online user experience ,user behavior ,micro-moments, mobile devices, online user experience, user behavior - Abstract
In recent years, in the advent of global internet availability and almost equally omnipresent mobile device usage, online user behavior together with the resulting experience has been changing and evolving at a significant pace. Users do not only spend more time online, they consult online resources and seek information for various goals and are motivated by a variety of needs: those intent-driven actions are dispersed throughout the day (or night) and integrated within their daily activities. The user behavior is determined by specific micro- moments which are truly the moments of consumer needs and therefore the moments the marketers need to be a part of. Furthermore, mobile devices and smartphones in particular, possess the ability to promptly meet the immediate needs of their users thus shaping new opportunities for marketers to capture and utilize. In order to have a better understanding of online user intention and behavioral patterns, the paper provides an insight of recent studies of user micro-moments within the digital environment. The main goal of this paper is to provide an overview of recent academic and professional papers on the changes in online user experience and behavior and suggest the theoretical background for further research. Mobile devices can directly influence user behavior and emotional states by addressing a wide variety of information needs. The implications of these findings are important as they empower the possibilities of direct marketing in the digital era. more...
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- 2016
13. Resilience and the (micro-)dynamics of organizational ambidexterity: implications for strategic HRM
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Tony Wall, Neil Moore, Tony Ward, Peter Stokes, Suzanne Cronshaw, Caroline Rowland, and Simon M. Smith
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Organizational Behavior and Human Resource Management ,Knowledge management ,Strategy and Management ,media_common.quotation_subject ,Extremes ,N600 ,Organizational performance ,Adaptability ,Extant taxon ,Management of Technology and Innovation ,0502 economics and business ,Business ,N100 ,Sociology ,N200 ,Business and International Management ,Human resources ,Resilience (network) ,media_common ,Ambidexterity ,Marketing ,Resilience ,business.industry ,05 social sciences ,050209 industrial relations ,Micro-moments ,Dynamics (music) ,Industrial relations ,N210 ,business ,Organizational Ambidexterity ,HRM practices - Abstract
The file attached to this record is the author's final peer reviewed version. In the twenty-first century, resilience has emerged as an important topic linked to calls for adaptability, well-being and organizational performance. Extant strategic human resource management (HRM) literature and practices have developed many insights into resilience. However, overall, they have a propensity to conceptualise resilience as being associated with ‘macro-’ and ‘extreme’ situations. This paper complements the prevailing perspective by developing a micro-focus on resilience through the conceptual framework of organizational ambidexterity surfacing under-examined individual resilience in connection with HRM practices. Methodologically, the paper adopts a qualitative approach presenting data from two illustrative contexts: an ‘everyday’ quasi-governmental institution and a prima facie ‘extreme’ pan-international military organization. Using template analysis, a number of valuable themes and similarities are identified. The findings and discussion underline the managerial challenges in handling organizational ambidextrous dynamics and tensions surrounding resilience, positive and sceptical approaches in relation to individual and organizational stances towards HRM practices. As such, the results point at value in HRM managers and practices recontextualising and appreciating ‘extremes’ and resilience more as an everyday (rather than exceptional) phenomenon wherein myriad micro-moments are highly significant in constructing and influencing macro-contexts. This also implies a need to see cynical resistance as normative rather than automatically negatively. more...
14. sustAGE 1.0 – First Prototype, Use Cases, and Usability Evaluation
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Mallol, A., Varlamis, I., Pateraki, M., Lourakis, M., Athanassiou, G., Maniadakis, M., Papoutsakis, K., Papadopoulos, T., Semertzidou, A., Cummins, N., Schuller, B., Karolos, I., Pikridas, C., Patias, P., Vantolas, S., Kallipolitis, L., Werner, F., Ascolese, A., and Nitti, V. more...
- Subjects
IOT ,Artificial Intelligence ,Micro-Moments ,Ageing Workforce ,Personalised Recommendations - Abstract
Worldwide demographics are changing; we are living longer and, in developed countries, the birth-rate is dropping. In this context and motivated by the challenge of sustainable ageing, this paper presents sustAGE, a multi-modal person-centred IoT platform, which integrates with the daily activities of ageing employees both at work and outside. The sensed information allows the system to assess the state of the users and context-related aspects with the aim to provide timely recommendations to support wellbeing, wellness, and productivity. Herein, we describe the use cases, outline the overall system architecture, and introduce the first prototype of the platform implemented up-to-date. Furthermore, the results from the usability evaluation conducted with real users who used the prototype for one month are presented. more...
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