arXiv:2606.01229v1 Announce Type: new Abstract: During green building design, computer-aided energy assessment is widely used to improve efficiency and achieve overall optimization. This paper presents a platform that combines Building Information Modeling (BIM), sensor operational data, and advanced simulation workflows using robust algorithms. The platform uses a multi-layer service architecture with dynamic energy simulation and evolutionary multi-objective optimization, connected via a high-performance C++ core and adaptive agent models. A mid-rise office building was selected as the case
The increasing focus on sustainability and energy efficiency in new constructions, coupled with advancements in AI and simulation technologies, makes this development timely.
Sophisticated readers should care as the integration of AI-driven platforms like this can significantly optimize energy consumption in built environments, contributing to broader energy goals and potentially creating new industry standards.
The design process for 'green buildings' can become significantly more efficient and effective through the use of integrated AI, BIM, and sensor data for dynamic optimization.
- · Green building developers
- · Smart city technology providers
- · Energy management software companies
- · AI/ML algorithm developers
- · Traditional building design firms
- · Inefficient construction practices
- · Energy-intensive building material suppliers
Widespread adoption of AI-driven platforms for building design leads to a reduction in energy consumption for new constructions.
Increased demand for sensor integration and data analytics in real estate, driving innovation in smart building technologies.
Potential for regulatory changes mandating such energy-efficient design approaches, accelerating the green building market.
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Read at arXiv cs.AI