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

**TRUST2**是一个工业研究项目，旨在加快人工智能(AI)在建筑管理中的应用。尽管人工智能具有潜在的影响，但由于对其有效性和可靠性缺乏信任，建筑行业的决策者对是否进行必要的投资并采用人工智能犹豫不决。经理和业主需要看到令人信服的真实世界演示，证明AI/ML系统节省资金和能源，保持运营效率，人们舒适和安全，在与他们自己相似的建筑中。系统集成商也不想因为向客户推荐未经验证的技术而冒着声誉的风险。尽管存在风险，但在建成环境中投资人工智能的潜在回报是巨大的。随着能源价格的上涨，企业现在越来越担心控制能源成本，而不是出于可持续性的考虑。其他运营效率也是可以实现的，从空间利用到人力。**TRUST2**旨在展示人工智能在建筑管理中的好处，特别是在英国，尽管智能建筑行业是AI/ML创新的领先者，但在英国，智能建筑行业在采用方面落后于人。这个第二阶段的项目利用传感器和其他数据的洞察力，将人工智能和机器学习作为回路中的专家来控制选定的建筑管理系统。这些技术在现有建筑中的第二阶段实际应用将在现场演示、案例研究、科学论文和文章中进行评估和强调，以增加人们对在建筑管理中使用人工智能的信任，并减少行业采用的障碍。

**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.