Five papers published on Zenodo covering the AI models, scoring methodology and compliance frameworks behind SenseCore. Open access, citable.
Application of Temporal Fusion Transformer architecture to the Building Data Genome 2 dataset, achieving sub-11% MAPE across 1,112 commercial buildings.
Z-Score, IQR and Isolation Forest ensemble methods for surfacing waste and inefficiency in half-hourly consumption data, with cost-impact estimation.
Methodology for a proprietary tenant-level risk score combining EPC band, consumption patterns, household indicators and intervention history.
Unsupervised occupancy detection from consumption patterns, used to improve forecast accuracy across commercial and public estates.
A framework for automating SECR Scope 1 and 2 reporting with audit-versioned outputs and live DEFRA factor updates.
A practical guide to Scope 1 + 2 carbon reporting under the Streamlined Energy and Carbon Reporting framework. Includes worked examples and a SECR-ready checklist.
Read guide →What's new in ESOS Phase 4, who needs to comply, and how to assemble the required evidence pack without three months of consultant time.
Read guide →How to push half-hourly readings into SenseCore via REST API, CSV upload, or smart meter integration. SDK examples in Python and TypeScript.
Read guide →Endpoint-by-endpoint walkthrough with curl, Python and TypeScript examples. X-API-Key authentication, rate limits, error envelopes documented.
Read guide →Briefing note on how UK councils are using AI energy intelligence to meet SECR obligations, manage housing stock and reduce operational spend in a constrained budget environment.
Read briefing →How NHS Trusts can move from passive ERIC reporting to active estate decarbonisation — with a framework for prioritising interventions across complex hospital sites.
Read briefing →All SenseCore papers are published open-access on Zenodo with permanent DOIs. Cite freely in academic work, procurement documents and policy submissions.
@article{ayoola2026tft,
title = {Temporal Fusion Transformer for
Building Electricity Forecasting},
author = {Ayoola, Olajide},
journal = {Zenodo},
year = {2026},
doi = {10.5281/zenodo.sensecore-tft},
url = {https://zenodo.org/communities/sensecore}
}