New Perspectives and Holistic Developments in Built Environment: Interlacing Artificial Intelligence, Lighting Design and Power Quality Management

About this Research Topic

Background

People spend the majority of their time indoors. Recent rapid developments in the disciplines of Architecture, Civil Engineering, Illumination Engineering, Facilities Management, and Building Services Engineering have greatly augmented the experience of occupants in built environments. Researchers have explored various factors and attributes of indoor spaces and how these contribute to human comfort, work efficiency, and subjective satisfaction.

The past two decades have witnessed significant technological advancements, especially in artificial intelligence (AI) and machine learning (ML). These tools enable ongoing upgrades in indoor facilities and the enhancement of Indoor Environmental Quality (IEQ) through simulation, post-occupancy evaluation, and data-driven solutions. Topics such as visual comfort, energy-efficient lighting solutions, and demand-side management of electrical loads are at the forefront of global research, often facilitated by novel applications of computer science and AI.

Objective

This Research Topic aims to unite and interlace novel, innovative, and cutting-edge methods stemming from the latest advancements across multiple STEM fields:

o Computer Science
o Electrical Engineering
o Architecture
o Civil Engineering
o Illumination Engineering

The overall goal is to enhance human comfort and wellbeing in built environments, with an emphasis on:

o Characterizing domestic and commercial electrical loads and their effects on grid stability;
o Demand-side management and peak electricity demand forecasting;
o Impact and transition to human-centric LED lighting and salubrious lighting design;
o Integration and evaluation of passive solar and daylighting strategies;
o AI and ML for energy efficiency, power quality, and smart scheduling;
o IoT-based smart lighting and load management.


Scope and Topics of Interest

Authors are encouraged to submit full-length research papers, reviews, and case studies on (but not limited to) the following topics:

o Domestic electrical load characterization and power quality assessment
o Demand side management of domestic and industrial electrical loads
o Indoor lighting solutions, lighting control, and optimization
o Ergonomics and human factors
o Facilities management
o Visual and cognitive performance of occupants in various illumination settings
o AI/ML applications for electric load scheduling and energy efficiency assessment
o Daylighting design, methods, and applications
o Performance evaluation of louvers, windows, skylights, and other daylighting devices
o Smart lighting in indoor spaces and IoT-based load management
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Submission Information
We welcome submissions that demonstrate novel research outcomes, comprehensive reviews, and detailed case studies aligning with the topics above.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Editorial
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Editorial
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review

Keywords: Artificial Intelligence, Indoor Lighting, Power Quality, Demand Side Management, Facilities Management, Daylighting, Load Scheduling, Visual Comfort, Energy Efficiency

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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