Search results “Data mining energy management”
How a Startup Brought Energy Efficiency to NYC with Machine Learning and Chatbots
The core features comprising Watson Data Platform, Data Science Experience and Data Catalog on IBM Cloud, with additional embedded AI services, including machine learning and deep learning, are now available in Watson Studio and Watson Knowledge Catalog. Get started for free at http://ibm.co/watsonstudio BlocPower data scientists depend on machine learning, powered by IBM Watson Data Platform, to perform comprehensive energy audits of buildings across New York City. After analysis is complete, building owners then learn how to improve their energy efficiency and lower energy costs through interactions with BlocPower’s intuitive chatbot, built with Watson Conversation Service and Watson Visual Recognition. See what you can build and discover with IBM Watson Data Platform: ibm.co/watsondataplatform IBM Owner: Jim Young
Views: 1123 IBM Developer
Intelen Stream Web Data mining on Energy Smart Metering (Energy Analytics by Intelen)
Using advanced web data and stream mining Algorithms, we perform on-line stream analysis and smart monitoring of a Boiling Kettle. Every 6 sec, weighted clustering is being performed and statistical indices are analysed on the energy data stream, indicating hidden patters and trends of the device or behavioral use... Our device used Current Cost ENVI meter over cable connection...coming up the wireless one...
Views: 1515 IntelenGroup
IEEFA Webinar: Power Plant Data Mining
Director of Resource Planning Analysis, David Schlissel, and Visual Information Designer, Seth Feaster, discuss power plant data mining. Recorded March 02, 2017. Slides can be viewed at: https://tinyurl.com/IEEFAwebinar2
Views: 105 IEEFA.org
Website: https://bluenote.world Whitepaper: https://static.icoholder.com/files/20703/e1f5ff6c690f7accc8f5de4f1a8841e6.pdf ANN thread: https://bitcointalk.org/index.php?topic=5079953.0 Telegram: https://t.me/bluenoteworld Facebook: https://www.facebook.com/bluenote.world Twitter: https://twitter.com/bluenote_world Bluenote is the largest source of climate change due to energy consumption, which accounts for about 33% of global greenhouse gas emissions. Fortunately, all buildings can reduce the amount of energy used by intelligent management, data mining, the introduction of advanced energy technologies. These improvements can make the building more useful. Bluenote runs the platform with open data and acquires the building in which precisely specifies the way of reducing energy consumption, reducing emissions, increasing the cost of buildings and lack of emissions in the world. #blockchain #Bluenote #climatechange #crowdfunding #energyefficiency Автор ETH address: 0x5Cd2bE47A0979abdd30835eF6c9d515aC2167b2B Профиль форума: https://bitcointalk.org/index.php?action=profile;u=1351292
Views: 609 BEST ICO
Big data for greater energy efficiency (DSMU32)
Data streams relevant for energy use in buildings are increasing. Many households have “smart” meters in place or are installing smart thermostats or smart plugs; and the first IoT applications are entering households. We see similar developments in commercial buildings. This wealth of data provides new opportunities to better understand and control energy use in buildings. Significant energy saving potentials are claimed. Nevertheless, there are also serious challenges, like privacy and cybersecurity issues, and the variety of platforms. In this webinar an overview will be given of the main developments in this new field. The challenge is how big data can empower users of homes and office buildings to create a comfortable and efficient living and working place.
Views: 486 Leonardo ENERGY
Energy Company of the Future: The Digitization of Onshore
Changes in the Energy industry, means oil and gas companies need to adjust to a new paradigm to remain competitive and relevant in the future. This video provides a deeper dive into the exploration and production digitization of the oil field. Learn more at https://www.accenture.com/energycofuture
Views: 14216 Accenture
Studying Energy Systems and Data Analytics at UCL
The MSc in Energy Systems and Data Analytics provides an academically leading and industrially relevant study of energy systems through the lens of data analytics. Taught by experts at University College London's prestigious Energy Institute, the MSc ESDA is the first programme of its kind in the UK, combining the study of Energy Systems with Data Science. As an ESDA student, you will gain a multi-sector multi-vector understanding of Energy Systems, while developing advanced statistical and machine learning skills and getting practical experience of data analysis. The programme is aimed at students with a quantitative background who have an interest in energy and are motivated by the use of data science to solve sustainability problems. You will gain skills sought after by industry allowing you to become a leader and innovator in the energy sector, from established large scale utilities and data science companies to innovative new start-ups. Learn more: https://www.ucl.ac.uk/bartlett/energy/programmes/msc-energy-systems-and-data-analytics
Views: 1609 UCLEnergyInstitute
Data Management_ Oncor Meter Data Management - Outage Management System Integration
Help with inventory management? for my small business, need help updating data? sheet? looking for software!? How to change file system from ntfs to fat32 while keeping the data? on the drive? Which is better a mba in project management? or go for a (mpm) masters in project management? degree? Is it worth the time and energy to pursue a master is degree in sports management? Would a certificate in business management? help me get into grad school? does it add any value? Will increasing the logical drive size from adding an additional drive into an array cause me to lose my data? Whats your idea is on a time management? program? i want to hear your thoughts? What is the best method of inventory management? in auto component (gears, axles & shaft) manufacturing company? Recover data? off of a corrupted hdd? How do i ensure that the result of an if statement in excel doesnt exceed a certain number? Which is good subject network management? or data? mining? Report on data? management? Why am i having re-occuring nightmares about gr.12 math? Data? flow diagram of hospital management? system according to system development life cycle?
EcoStruxure & Internet of Things (IoT) for Innovation and Energy Management | Schneider Electric
At Schneider Electric, we aim to improve your business by using EcoStruxure Platform, our IoT-enabled system that leverages Microsoft Azure technology to optimize your operations. Our platform will help you manage energy efficiency and business operations through our state-of-the-art IT technology. With EcoStruxure, you can experience innovation at every level. ►Click here to watch more EcoStruxure videos: https://bit.ly/2JfXNA9 ►Click here to learn more about EcoStruxure: https://www.schneider-electric.com/en/work/campaign/innovation/overview.jsp ►Click here to subscribe to Schneider Electric: http://www.youtube.com/subscription_center?add_user=SchneiderCorporate Connect with Schneider Electric: ►Global Website: https://www.schneider-electric.com/ww/en/ ►Job Opportunities: https://www.schneider-electric.com/en/about-us/careers/overview.jsp ►Facebook: https://www.facebook.com/SchneiderElectricUS ►Twitter: https://twitter.com/SchneiderElec ►LinkedIn: https://www.linkedin.com/company/schneider-electric ►Instagram: https://instagram.com/schneiderelectric/ ►Pinterest: https://www.pinterest.com/schneiderelec/ ►Visit our blog: https://blog.schneider-electric.com/ This video is an overview of Schneider Electric's EcoStruxure Platform.
Views: 24926 Schneider Electric
Real Time Energy Management
Dr. Carol Miller, Wayne State University, demonstrates how the Real Time Energy Monitoring project team is using the Smart Grid to mine Big Data for environmental benefits. The Great Lakes Protection Fund supported the project because they saw the order of magnitude consequence for providing the public with some options to change their energy use to coincide with clean power sources.
Views: 107 Ravenswood Media
Mike Glass: Emerging Uses for Data & Analytics in Utilities
Mike Glass is Director, Demand Side Systems at PG&E. Held at the Haas School of Business, University of California, Berkeley, the Data Science & Strategy Lecture Series examines the evolving role of "big data" and analytics in managerial decision-making. In this playlist, lecture series host Prof. Greg La Blanc interviews industry executives and practitioners on key topics in data science, including data mining, machine learning, visualization, advanced statistics and more. For more information please visit: http://businessinnovation.berkeley.edu/data-science-strategy/lecture-series/.
Views: 1926 Berkeley Haas
Smart Home Energy Management Market   Patent Analysis and Vendors Strategies Analyzed
Smart Home Energy Management Market - Patent Analysis and Vendors Strategies Analyzed report provide Major technology fields and sectors of 3,495 smart home energy management patents identified using data mining technique. Buy a copy of report @ http://www.reportsnreports.com/Purchase.aspx?name=458648 for US $2500.
Views: 4 Lisa Scott
OSIsoft: My PI Story - Goldcorp
At Goldcorp the PI System is helping to improve metal recovery. Superintendent of Electrical, Instrumentation, Process Control, & Energy Management Derek Shuen explains. At https://www.osisoft.com/Presentations/Real-Time-Data-Critical-to-Mining/ watch his full conference presentation "Real Time Data Critical to Mining."
Views: 316 OSIsoftNews
Putting Data to Work - Data Driven Energy Management
The May 25 forum Putting Data to Work: Harness Your Building Metrics to Improve Performance provided a wealth of knowledge around the latest insights into how data integration and analysis, use of interval data, and maintenance of energy management systems can be used to reduce energy use and increase savings. Shawn Thompson presented on utilizing data to create profitable energy management projects.
Big data brings massive energy savings to commercial buildings | Demand Logic, UK Ashden Award
http://www.ashden.org/winners/DemandLogic15 Mining the information generated by most building management systems (BMS) is usually like looking for a needle in a haystack, with many businesses wasting huge opportunities to save energy and money. But Demand Logic has created a cloud-based system that plugs into the BMS and quickly identifies what it describes as ‘energy insanities’, like rooms being heated and cooled at the same time, or faulty equipment. Demand Logic then works with the building management team to develop a plan to fix them. This can generate huge savings: one of Demand Logic’s clients, Kings College in London, has cut an estimated £390,000 off its £5m annual energy bill.
Views: 920 Ashden
Divide & Conquer Methods for Big Data Analytics
Data is being generated at a tremendous rate in modern applications as diverse as internet applications, genomics, health care, energy management and social network analysis. There is a great need for developing scalable methods for analyzing these data sets. In this talk, I will present some new Divide-and-Conquer algorithms for various challenging problems in large-scale data analysis. Divide-and-Conquer has been a common paradigm that has been widely used in computer science and scientific computing, for example, in sorting, scalable computation of n-body interactions via the fast multipole method and eigenvalue computations of symmetric matrices. However, this paradigm has not been widely employed in problems that arise in machine learning. I will introduce some recent divide-and-conquer methods that we have developed for three representative problems: (i) classification using kernel support vector machines, (ii) dimensionality reduction for large-scale social network analysis, and (iii) structure learning of graphical models. For each of these problems, we develop specialized algorithms, in particular, tailored ways of "dividing" the problem into subproblems, solving the subproblems, and finally "conquering" them. It should be noted that the subproblem solutions yield localized models for analyzing the data; an intriguing question is whether the hierarchy of localized models can be combined to yield models that are not only easier to compute, but are also statistically more robust. This is joint work with Cho-Jui Hsieh, Pradeep Ravikumar, Donghyuk Shin and Si Si.
Views: 310 Microsoft Research
Data Science role in Building Smart City
This video helps u to know about the data mining prediction and its use in building in smart city R language Python
Maximize Plant Performance: Data Mining to Implement a Better O&M Strategy
In this webinar AWS Truepower President, Dr. Bruce Bailey, and Chief Engineer, Daniel Bernadett, discuss how performance issues can be addressed through diagnostic data mining. They share a case study demonstrating how the implementation of diagnostic techniques led to increased overall performance at a wind facility by modifying the operations and maintenance strategy.
Views: 589 AWS Truepower
Energy Management and Goal Setting Q&A
As part of my #FuelGood Campaign with Whole Earth peanut butter this month, I did a Facebook live. I answered a whole bunch of different questions and shared my experiences and advice around achieving different types of fitness, health, lifestyle and adventure goals. If you have any more questions leave them in the comments below
Views: 573 Challenge Sophie
Energy Efficiency Data Tracking and Reporting Software Platform : DSMTracker
Energy Efficiency programs are complex. DSMTracker is a next generation platform that enables the planning, management, design and tracking of energy efficiency and demand response programs.
Energy Invesemtent Analysis: Cash Flow for Solar Power
This description covers several advanced cash flow topics used when creating a cash flow for solar power systems. This video is part of an energy investment analysis class in the Energy Management and Renewable Energy Solar Programs at Delaware Technical and Community College. To see a full playlist of the Energy Investment Analysis videos go here: https://www.youtube.com/playlist?list=PL1gduOjl1EholWYe-RlxUDPVSSCWiwYm1 To follow along with the slides (feel free to comment on them with questions/suggestions!) go here: https://docs.google.com/presentation/d/11Kz0yGLrLlHgOfwdnLX1UYwak43nTMXinOUunDzAuLY/edit?usp=sharing For more details about the Energy Management program go here: https://www.dtcc.edu/academics/programs-study/energy-management. For more details about the renewable energy solar program go here: https://www.dtcc.edu/academics/programs-study/renewable-energy-solar. For more information about me go to my personal website here: http://bit.ly/corybud
Views: 465 Cory Budischak
"Cybersecurity and its Impacts on Installation Energy Management" Webinar
SERDP-ESTCP Webinar Series 10/06/2016
Views: 108 SERDP and ESTCP
Storing renewable energy for Italy's biggest data centre campus – Hitachi
FIAMM (a Hitachi group company) and Aruba have created a novel solution to power Italy’s largest data centre using only renewable energy, enabling the local communities to enjoy all the benefits of a connected lifestyle and the comfort of knowing they aren’t impacting the environment.
Views: 952 HitachiBrandChannel
Billion Electric | The Future is Now | Energy Management
We enhance life and environmental sustainability through combing ICT and energy monitoring technologies to develop intelligent IoT solutions for Energy Management, Lighting Control, and Smart Grid applications. More information on Billion: http://www.billion.com/ Smart Energy Saving Solution: http://www.billion.com/about/Solutions/Smart%20Energy Smart Lighting Control Solution: http://www.billion.com/about/Solutions/Smart%20Lighting Smart Grid AMI, BPL, and EoC Solution: http://www.billion.com/about/Solutions/Smart%20Grid
Views: 516 Billion Electric
McKinsey Careers: Mining with the Global Energy & Materials practice
Several of our colleagues describe their passion for mining and the industry's big toys, large-scale impact, and an unprecedented need for enormous amounts of innovation.
Views: 1508 McKinsey & Company
Big Data from Space: Actionable Intelligence on Earth
Big Data from Space: Actionable Intelligence on Earth Date(s) - Wed Oct 22, 2014 6:00 pm - 8:30 pm Location Stanford GSB: Cemex Auditorium at the Knight Management Center Dramatic disruptions to Earth observation are being delivered by ambitious startups that are launching large fleets of small, interconnected satellites and developing cutting-edge analytics. The number of earth-gazing satellites has nearly doubled in 2014 alone. With views into daily global activity being refreshed at a faster rate than ever before, selling raw pixels and signals is not enough to satisfy industry demands. It is these startups that are changing how we use Big Data in business here on earth. Responding to ever-expanding industry demands by delivering “near real-time” data and developing cutting-edge analytics at a lower cost, these startups are providing actionable insights for many industries. Finance, insurance, agriculture, forestry, fishing, mapping, manufacturing, shipping, mining, sustainable industries, and energy enterprises are using eyes and ears in the sky to make better decisions and improve operational efficiency with actionable data sent ultimately from space. As funding moves rapidly from government to commercial, the global market for satellite-sourced intelligence is predicted to grow by over $5 billion by 2019. Venture capital firms such as DFJ Venture and Khosla Ventures are investing in innovative startups, with successful exits like the recent acquisitions of satellite operator Skybox Imaging by Google for $500 million and climatology Big Data analytics venture The Climate Corporation by Monsanto for nearly $1 billion. Why are industry giants eager to consume data from the sky? Which markets will be transformed using Big Data from Space? Join us on Wednesday October 22, 2014 to find out. Moderator: Amaresh Kollipara, Principal, Space Angels Network, and Managing Partner, Earth2Orbit Panelists: Pavel Machalek, CEO, Spaceknow Theresa Condor, Vice-President Sales & Business Development, Spire Robbie Schingler, Co-Founder, President and COO, Planet Labs Shay Har-Noy, Ph.D, Senior Director – Geo-spatial Big Data, DigitalGlobe Julian Mann, Co-Founder and Vice-President Product Management, Skybox Imaging (acquired by Google) Demo Companies**: Mapbox | Spaceknow | DauriaGEO | UrtheCast | Alanax | Silicon Valley Space Center | SETI ** Follow (@VLAB) on Twitter and Event Hashtag #VLABsi
Views: 18204 vlabvideos
Prediction of effective rainfall and crop water needs using data mining techniques
Prediction of effective rainfall and crop water needs using data mining techniques- IEEE PROJECTS 2018 Download projects @ www.micansinfotech.com WWW.SOFTWAREPROJECTSCODE.COM https://www.facebook.com/MICANSPROJECTS Call: +91 90036 28940 ; +91 94435 11725 IEEE PROJECTS, IEEE PROJECTS IN CHENNAI,IEEE PROJECTS IN PONDICHERRY.IEEE PROJECTS 2018,IEEE PAPERS,IEEE PROJECT CODE,FINAL YEAR PROJECTS,ENGINEERING PROJECTS,PHP PROJECTS,PYTHON PROJECTS,NS2 PROJECTS,JAVA PROJECTS,DOT NET PROJECTS,IEEE PROJECTS TAMBARAM,HADOOP PROJECTS,BIG DATA PROJECTS,Signal processing,circuits system for video technology,cybernetics system,information forensic and security,remote sensing,fuzzy and intelligent system,parallel and distributed system,biomedical and health informatics,medical image processing,CLOUD COMPUTING, NETWORK AND SERVICE MANAGEMENT,SOFTWARE ENGINEERING,DATA MINING,NETWORKING ,SECURE COMPUTING,CYBERSECURITY,MOBILE COMPUTING, NETWORK SECURITY,INTELLIGENT TRANSPORTATION SYSTEMS,NEURAL NETWORK,INFORMATION AND SECURITY SYSTEM,INFORMATION FORENSICS AND SECURITY,NETWORK,SOCIAL NETWORK,BIG DATA,CONSUMER ELECTRONICS,INDUSTRIAL ELECTRONICS,PARALLEL AND DISTRIBUTED SYSTEMS,COMPUTER-BASED MEDICAL SYSTEMS (CBMS),PATTERN ANALYSIS AND MACHINE INTELLIGENCE,SOFTWARE ENGINEERING,COMPUTER GRAPHICS, INFORMATION AND COMMUNICATION SYSTEM,SERVICES COMPUTING,INTERNET OF THINGS JOURNAL,MULTIMEDIA,WIRELESS COMMUNICATIONS,IMAGE PROCESSING,IEEE SYSTEMS JOURNAL,CYBER-PHYSICAL-SOCIAL COMPUTING AND NETWORKING,DIGITAL FORENSIC,DEPENDABLE AND SECURE COMPUTING,AI - MACHINE LEARNING (ML),AI - DEEP LEARNING ,AI - NATURAL LANGUAGE PROCESSING ( NLP ),AI - VISION (IMAGE PROCESSING),mca project NETWORKING 1. A Non-Monetary Mechanism for Optimal Rate Control Through Efficient Cost Allocation 2. A Probabilistic Framework for Structural Analysis and Community Detection in Directed Networks 3. A Ternary Unification Framework for Optimizing TCAM-Based Packet Classification Systems 4. Accurate Recovery of Internet Traffic Data Under Variable Rate Measurements 5. Accurate Recovery of Internet Traffic Data: A Sequential Tensor Completion Approach 6. Achieving High Scalability Through Hybrid Switching in Software-Defined Networking 7. Adaptive Caching Networks With Optimality Guarantees 8. Analysis of Millimeter-Wave Multi-Hop Networks With Full-Duplex Buffered Relays 9. Anomaly Detection and Attribution in Networks With Temporally Correlated Traffic 10. Approximation Algorithms for Sweep Coverage Problem With Multiple Mobile Sensors 11. Asynchronously Coordinated Multi-Timescale Beamforming Architecture for Multi-Cell Networks 12. Attack Vulnerability of Power Systems Under an Equal Load Redistribution Model 13. Congestion Avoidance and Load Balancing in Content Placement and Request Redirection for Mobile CDN 14. Data and Spectrum Trading Policies in a Trusted Cognitive Dynamic Network Architecture 15. Datum: Managing Data Purchasing and Data Placement in a Geo-Distributed Data Market 16. Distributed Packet Forwarding and Caching Based on Stochastic NetworkUtility Maximization 17. Dynamic, Fine-Grained Data Plane Monitoring With Monocle 18. Dynamically Updatable Ternary Segmented Aging Bloom Filter for OpenFlow-Compliant Low-Power Packet Processing 19. Efficient and Flexible Crowdsourcing of Specialized Tasks With Precedence Constraints 20. Efficient Embedding of Scale-Free Graphs in the Hyperbolic Plane 21. Encoding Short Ranges in TCAM Without Expansion: Efficient Algorithm and Applications 22. Enhancing Fault Tolerance and Resource Utilization in Unidirectional Quorum-Based Cycle Routing 23. Enhancing Localization Scalability and Accuracy via Opportunistic Sensing 24. Every Timestamp Counts: Accurate Tracking of Network Latencies Using Reconcilable Difference Aggregator 25. Fast Rerouting Against Multi-Link Failures Without Topology Constraint 26. FINE: A Framework for Distributed Learning on Incomplete Observations for Heterogeneous Crowdsensing Networks 27. Ghost Riders: Sybil Attacks on Crowdsourced Mobile Mapping Services 28. Greenput: A Power-Saving Algorithm That Achieves Maximum Throughput in Wireless Networks 29. ICE Buckets: Improved Counter Estimation for Network Measurement 30. Incentivizing Wi-Fi Network Crowdsourcing: A Contract Theoretic Approach 31. Joint Optimization of Multicast Energy in Delay-Constrained Mobile Wireless Networks 32. Joint Resource Allocation for Software-Defined Networking, Caching, and Computing 33. Maximizing Broadcast Throughput Under Ultra-Low-Power Constraints 34. Memory-Efficient and Ultra-Fast Network Lookup and Forwarding Using Othello Hashing 35. Minimizing Controller Response Time Through Flow Redirecting in SDNs 36. MobiT: Distributed and Congestion-Resilient Trajectory-Based Routing for Vehicular Delay Tolerant Networks
Data Mining Projects 2016-2017 | ieee data mining papers 2016
ieee data mining papers 2016 for ME,M.Tech.,M.Phil., Ph.D., B.E, B.Tech., MCA A Novel Recommendation Model Regularized with User Trust and Item Ratings Automatically Mining Facets for Queries from Their Search Results Booster in High Dimensional Data Classification Building an intrusion detection system using a filter-based feature selection algorithm Connecting Social Media to E-Commerce: Cold-Start Product Recommendation Using Microblogging Information Cross-Domain Sentiment Classification Using Sentiment Sensitive Embeddings Crowdsourcing for Top-K Query Processing over Uncertain Data Cyberbullying Detection based on Semantic-Enhanced Marginalized Denoising Auto-Encoder Domain-Sensitive Recommendation with User-Item Subgroup Analysis Efficient Algorithms for Mining Top-K High Utility Itemsets Efficient Cache-Supported Path Planning on Roads Mining User-Aware Rare Sequential Topic Patterns in Document Streams Nearest Keyword Set Search in Multi-Dimensional Datasets Rating Prediction based on Social Sentiment from Textual Reviews Location Aware Keyword Query Suggestion Based on Document Proximity Using Hashtag Graph-based Topic Model to Connect Semantically-related Words without Co-occurrence in Microblogs Quantifying Political Leaning from Tweets, Retweets, and Retweeters Relevance Feedback Algorithms Inspired By Quantum Detection Sentiment Embeddings with Applications to Sentiment Analysis Top-Down XML Keyword Query Processing TopicSketch: Real-time Bursty Topic Detection from Twitter Top-k Dominating Queries on Incomplete Data Understanding Short Texts through Semantic Enrichment and Hashing To get this project in ONLINE or through TRAINING Sessions, Contact: JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83.Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai,Thattanchavady, Puducherry -9.Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690, Email: [email protected], web: www.jpinfotech.org, Blog: www.jpinfotech.blogspot.com
Application and Modeling of Battery Energy Storage in Power Systems||ieee 2018 power system projects
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Mining Human Activity Patterns from Smart Home Big Data for Healthcare Applications
Mining Human Activity Patterns from Smart Home Big Data for Healthcare Applications To get this project in ONLINE or through TRAINING Sessions, Contact: JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83.Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #37, Kamaraj Salai,Thattanchavady, Puducherry -9.Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690, Email: [email protected], web: http://www.jpinfotech.org Nowadays, there is an ever-increasing migration of people to urban areas. Health care services is one of the most challenging aspects that is greatly affected by the vast influx of people to city centers. Consequently, cities around the world are investing heavily in digital transformation in an effort to provide healthier ecosystem for people. In such transformation, millions of homes are being equipped with smart devices (e.g. smart meters, sensors etc.) which generate massive volumes of fine-grained and indexical data that can be analyzed to support smart city services. In this paper, we propose a model that utilizes smart home big data as a means of learning and discovering human activity patterns for health care applications. We propose the use of frequent pattern mining, cluster analysis and prediction to measure and analyze energy usage changes sparked by occupants’ behavior. Since people’s habits are mostly identified by everyday routines, discovering these routines allows us to recognize anomalous activities that may indicate people’s difficulties in taking care for themselves, such as not preparing food or not using shower/bath. Our work addresses the need to analyze temporal energy consumption patterns at the appliance level, which is directly related to human activities. For the evaluation of the proposed mechanism, this research uses the UK Domestic Appliance Level Electricity dataset (UK-Dale) - time series data of power consumption collected from 2012 to 2015 with time resolution of six seconds for five houses with 109 appliances from Southern England. The data from smart meters are recursively mined in the quantum/data slice of 24 hours, and the results are maintained across successive mining exercises. The results of identifying human activity patterns from appliance usage are presented in details in this paper along with accuracy of short and long term predictions.
Governance - Going Beyong Data Mining: Building a City Data Strategy
The increasing amount of data that local governments can collect is much more than a bunch of numbers and figures. It’s a vital infrastructure helping managers make better decisions and promote wider data-led innovation. However, going beyond mere collection and fine-tuning data schemes considering purpose and use is still a challenge. How to recognize city data as a city infrastructure underlying a data strategy? Keywords: data maturity; open data; policy framework; public services; cloud; policy framework; multilevel governance; techno-politics of data; data-driven; dataism; unplugging; multi-stakeholders; penta-helix MODERATOR Esteve Almirall Director of Center for Innovation in Cities ESADE Business & Law School SPEAKERS Igor Calzada Lecturer & Senior Research Fellow University of Oxford Konstantinos Champidis Chief Digital Officer City of Athens Stefano De Panfilis Chief Operations Officer FIWARE Foundation José Antonio Rubio Blanco Data & Algorithms Leader MINSAIT by INDRA Save The Date 📅November 19-21 2019📅 Check out our website for further details: http://www.smartcityexpo.com/home If you wish to attend, check out our passes: http://www.smartcityexpo.com/en/visit/passes-and-prices Also, follow us on our other social media platforms Twitter: https://twitter.com/smartcityexpo Facebook: https://www.facebook.com/SmartCityExpoWorldCongress Linkedin: https://www.linkedin.com/in/smartcityexpo/ Instagram: https://www.instagram.com/smartcityexpo/
Tracking Energy Consumption and Cost with Noesis: Year Over Year
http://www.noesisenergy.com In this video you will learn how to track year over year trends by: •Visualizing custom year over year trends •Analyzing at the portfolio, facility, utility, and meter level © 2013 Noesis Energy Management
Views: 186 Noesis Financing
Following the electrons: methods for power management in commercial buildings (KDD 2012)
Following the electrons: methods for power management in commercial buildings KDD 2012 Gowtham Bellala Manish Marwah Martin Arlitt Geoff Lyon Cullen Bash Commercial buildings are significant consumers of electricity. The first step towards better energy management in commercial buildings is monitoring consumption. However, instrumenting every electrical panel in a large commercial building is expensive and wasteful. In this paper, we propose a greedy meter (sensor) placement algorithm based on maximization of information gained, subject to a cost constraint. The algorithm provides a near-optimal solution guarantee. Furthermore, to identify power saving opportunities, we use an unsupervised anomaly detection technique based on a low-dimensional embedding. Further, to better manage resources such as lighting and HVAC, we propose a semi-supervised approach combining hidden Markov models (HMM) and a standard classifier to model occupancy based on readily available port-level network statistics.
Rise of Big Data, Need for Energy Efficiency Drives Transformative Innovation ...
... in Data Center Industry Our society relies on data to overcome its toughest challenges, but now the volume of data is itself becoming a challenge. Transformational innovation is needed improve data center energy efficiency. https://www.businesswire.com/news/home/20180320006460/en/Rise-Big-Data-Energy-Efficiency-Drives-Transformative
Views: 42 BusinessWire
Predictive Data Mining For Sugar Crop Yield Prediction With Irrigation And Pesticide Usage Support
Predictive Data Mining Technique to correlate weather data with Sugar Crop pest density. This correlate the rules for best yield from Sugar Crop par acre area with current weather data to estimate the accurate requirement for Drip and Conventional irrigation, Asiphate PPM to ensure high yield.
Views: 2002 rupam rupam
Digital reinvention of mining
Barrick and Cisco are partnering for the digital reinvention of Barrick's business, bringing together cutting-edge technology and expertise to unleash the full potential of mining. In the first step of the collaboration, Barrick and Cisco will jointly develop a flagship digital operation at the Cortez mine in Nevada—embedding digital technology in every dimension of the mine to deliver better, faster, and safer mining. Building on the Cortez mine digitization experience, Cisco will support Barrick as it transforms its entire business over time—bringing digital technology to all of its mines as well as to its head office. Digital technology will also improve Barrick’s environmental and safety performance. Predictive data and analytics will improve management of energy, water, and emissions. Real-time data capture will allow the company to be even more transparent with, and accountable to, its local partners—for instance by providing water monitoring information in real time. And the use of digital technology will enhance Barrick’s permitting activities, further increasing transparency to stakeholders. As valuable as these new technologies will be in and of themselves, Barrick sees in them even deeper potential: to accelerate the cultural renewal already underway across the company. As Barrick has returned to its historical commitment to partnership, it has placed renewed emphasis on building and maintaining trust with its many stakeholders. The integration of digital technology into the heart of the business will allow Barrick to be all the more transparent with its partners. Furthermore, by embedding technology more deeply into the company, Barrick means to further reinvigorate its tradition as a bold, entrepreneurial company whose people are unafraid to challenge and surpass conventions.
Wind Power Big Data Analytics and IoT 2016, Berlin - Conference Video
A short edit from our successful Wind Power forum on 19th - 20th Oct. 2016 in Berlin, Germany. - Check our upcoming 'Renewable Energy' events: https://www.bisgrp.com/portfolio/upcoming-conferences?my=&in=renewable-energy - Event website: http://windpowerdata.global-renewableenergy-summit.com/ Video produced by 'video-nataceni.cz'
Views: 1172 BISGroupCom
Data Mining Paper Review
Recorded with http://screencast-o-matic.com
Views: 123 venu gopal valeti
High Salary Jobs in Canada - Part 1
High Paid jobs offered in Canada. How much professors, engineers, managers, teachers, technicians, nurses can earn in Canada. Link to High Salary Jobs in Canada - Part 2 https://youtu.be/oZgV528zGXg You can send your CV at: [email protected] Currently they provide job placements with good salaries. Jobs in Canada work in canada pilot jobs aircraft engineer jobs marketing manager jobs network engineer jobs computer engineer jobs nurses jobs cooks jobs waiters jobs teacher vacancies professor vacancies technician jobs engineer jobs
Views: 1877741 GoAbroad
Commuter Route Optimized Energy Management of Hybrid Electric Vehicles
Final Year IEEE Projects for BE, B.Tech, ME, M.Tech,M.Sc, MCA & Diploma Students latest Java, .Net, Matlab, NS2, Android, Embedded,Mechanical, Robtics, VLSI, Power Electronics, IEEE projects are given absolutely complete working product and document providing with real time Software & Embedded training...... ---------------------------------------------------------------- JAVA & .NET PROJECTS: Networking, Network Security, Data Mining, Cloud Computing, Grid Computing, Web Services, Mobile Computing, Software Engineering, Image Processing, E-Commerce, Games App, Multimedia, etc., EMBEDDED SYSTEMS: Embedded Systems,Micro Controllers, DSC & DSP, VLSI Design, Biometrics, RFID, Finger Print, Smart Cards, IRIS, Bar Code, Bluetooth, Zigbee, GPS, Voice Control, Remote System, Power Electronics, etc., ROBOTICS PROJECTS: Mobile Robots, Service Robots, Industrial Robots, Defence Robots, Spy Robot, Artificial Robots, Automated Machine Control, Stair Climbing, Cleaning, Painting, Industry Security Robots, etc., MOBILE APPLICATION (ANDROID & J2ME): Android Application, Web Services, Wireless Application, Bluetooth Application, WiFi Application, Mobile Security, Multimedia Projects, Multi Media, E-Commerce, Games Application, etc., MECHANICAL PROJECTS: Auto Mobiles, Hydraulics, Robotics, Air Assisted Exhaust Breaking System, Automatic Trolley for Material Handling System in Industry, Hydraulics And Pneumatics, CAD/CAM/CAE Projects, Special Purpose Hydraulics And Pneumatics, CATIA, ANSYS, 3D Model Animations, etc., CONTACT US: ECWAY TECHNOLOGIES 15/1 Sathiyamoorthi Nagar, 2nd Cross, Thanthonimalai(Opp To Govt. Arts College) Karur-639 005. TamilNadu , India. Cell: +91 9894917187. Website: www.ecwayprojects.com | www.ecwaytechnologies.com Mail to: [email protected]
Views: 143 Ecway Karur
Using Big Data Analysis as part of the Commissioning Process
The analysis of large volumes of historical data can be used to improve building performance. Video Courtesy: CxEnergy 2015 Presenter: Rick Rodriguez, Director, Portfolio & Innovation Building Performance & Sustainability, Building Technologies Division, Siemens Industry Abstract: As the marketplace continues to realize the value of commissioning a building to achieve performance enhancements, the role of technology within a commissioning strategy continues to evolve. The strategic benefit of analyzing large volumes of historical data to identify poor performance and implement improvement measures based on this data is clear, but the implementation of the strategy can take on many forms. This presentation will discuss research revealing three common myths associated with analytics for enterprise level energy management. Prior to adopting a big data solution to integrate into a commissioning strategy the myths have to be debunked: the solution has to fit with long-term goals, have the people and processes behind it, and output actionable information. Learn the details and scope of the research conducted as well as best practices when implementing a solution. This presentation was part of the 28-workshop technical program for CxEnergy 2015. Next year’s CxEnergy Conference & Expo will be held in Dallas, April 11-13. For more information, visit www.CxEnergy.com
Energy Analytics: Siemon Company
Siemon Company teamed up with Artis and Eversource using analytics software to take a deeper look at how their Watertown manufacturing plant uses energy.
Views: 255 energizect