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TRUST2 - Improving TRUST in artificial intelligence and machine learning for critical building management

TRUST2 - Improving TRUST in artificial intelligence and machine learning for critical building management
TRUST2 - 提高关键建筑管理的人工智能和机器学习的信任度
批准号:
10093095
负责人:
金额:
$93.87万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2024
资助国家:
英国
项目状态:
未结题
起止时间:
2024 至 --

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中文摘要
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英文摘要
**TRUST2** is an industrial research project that aims to accelerate the adoption of Artificial Intelligence (AI) in building management. Despite its potential impact, decision makers in the building industry are hesitant to make the investment required and adopt AI due to a lack of trust in its effectiveness and reliability. Managers and owners need to see convincing real-world demonstrations of AI/ML systems saving money and energy, keeping operations efficient, people comfortable and safe, in similar buildings to their own. System integrators also do not want to risk their reputation by recommending unproven technologies to their customers.Despite the risks, the potential payback for investment in AI in the built environment is significant. With rising energy prices, businesses are now increasingly concerned about controlling energy costs beyond sustainability reasons. Other operational efficiencies are also achievable, from space utilisation to manpower.**TRUST2** aims to demonstrate the benefits of AI in building management, particularly in the United Kingdom where the smart building industry lags behind in adoption despite being a leader in AI/ML innovation. This Phase 2 project utilises insights from sensor and other data with AI and machine learning as the expert in the loop to control selected building management systems. The Phase 2 real-world application of these technologies in an existing building will be evaluated and highlighted in live demonstrations, case studies, scientific papers, and articles to increase trust in the use of AI in building management and reduce barriers to adoption in the industry.
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Improving modelling of compact binary evolution.
  • 批准号:
    10903001
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    20.0万元
  • 批准年份:
    2009
  • 负责人:
    史蒂芬
  • 依托单位: