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  "author": "SMDH Data Science Team",
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  "author": "SMDH Data Science Team",
            
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  "author_email": "info@smdh.uk",
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  "author_email": "info@smdh.uk",
            
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"industrial-energy-consumption-dataset",
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"industrial-energy-consumption-dataset",
            
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  "creator_user_id": "06d04fb0-fe0e-4a6a-b958-061fb38a9f9c",
            
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  "groups": [],
            
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  "id": "4b669518-3fed-4845-9eb9-6353e84ac601",
            
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  "isopen": false,
            
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  "license_id": "other-nc",
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  "license_id": "other-nc",
            
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  "license_title": "Other (Non-Commercial)",
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  "license_title": "Other (Non-Commercial)",
            
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  "maintainer": "Dermot Kerr",
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  "maintainer": "Dermot Kerr",
            
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  "maintainer_email": "d.kerr@smdh.uk",
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  "maintainer_email": "d.kerr@smdh.uk",
            
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  "metadata_created": "2026-02-25T13:28:51.431295",
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  "metadata_created": "2026-02-25T13:28:51.431295",
            
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  "metadata_modified": "2026-02-25T13:29:36.024080",
            
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  "name": "ulster-university--industrial-energy-consumption-dataset",
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  "name": "ulster-university--industrial-energy-consumption-dataset",
            
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  "notes": "This dataset contains hourly Energy consumption 
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  "notes": "This dataset contains hourly Energy consumption 
            
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measurements for multiple industrial\r\nmeters across different 
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measurements for multiple industrial\r\nmeters across different 
            
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machines/processes from a single manufacturer. It is intended 
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machines/processes from a single manufacturer. It is intended 
            
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for\r\nuse in:\r\n\u2022 Energy analytics\r\n\u2022 
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for\r\nuse in:\r\n\u2022 Energy analytics\r\n\u2022 
            
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Forecasting\r\n\u2022 Anomaly detection\r\n\u2022 Industrial data 
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Forecasting\r\n\u2022 Anomaly detection\r\n\u2022 Industrial data 
            
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science applications\r\nEach row represents the aggregated energy 
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science applications\r\nEach row represents the aggregated energy 
            
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usage of a specific meter over a one-hour\r\ninterval.",
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usage of a specific meter over a one-hour\r\ninterval.",
            
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  "num_resources": 2,
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  "num_resources": 2,
            
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  "num_tags": 0,
            
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  "organization": {
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  "organization": {
            
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    "approval_status": "approved",
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    "approval_status": "approved",
            
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    "created": "2023-03-20T14:27:38.943709",
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    "created": "2023-03-20T14:27:38.943709",
            
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    "description": "Ulster University has a sustained track record in 
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    "description": "Ulster University has a sustained track record in 
            
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robotics, computer vision, and computational intelligence. Translating 
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robotics, computer vision, and computational intelligence. Translating 
            
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research into technologies that catalyse innovation in small and large 
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research into technologies that catalyse innovation in small and large 
            
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enterprises, we have been instrumental in attracting inward investment 
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enterprises, we have been instrumental in attracting inward investment 
            
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and developing the knowledge economy. Ulster lead SMDH, lead the 
33
and developing the knowledge economy. Ulster lead SMDH, lead the 
            
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virtual manufacturing platform and contribute to data science, 
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virtual manufacturing platform and contribute to data science, 
            
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roll-out and marketing.",
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roll-out and marketing.",
            
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    "image_url": "2023-05-02-104737.949700uu.png",
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    "is_organization": true,
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    "is_organization": true,
            
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    "name": "ulster-university",
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    "name": "ulster-university",
            
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    "state": "active",
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    "state": "active",
            
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    "title": "Ulster University",
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    "title": "Ulster University",
            
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    "type": "organization"
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    "type": "organization"
            
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  },
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"1/ulster-university/industrial-energy-consumption-dataset/Readme - 
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"1/ulster-university/industrial-energy-consumption-dataset/Readme - 
            
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Industrial Energy Consumption Dataset 1.pdf",
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Industrial Energy Consumption Dataset 1.pdf",
            
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  "title": "Industrial Energy Consumption Dataset",
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