In a recent event hosted by the Institute of Refrigeration (IOR), the integration of artificial intelligence (AI) and machine learning technologies within the cooling sector was explored. The discussion, led by IOR president Lisa-Jayne Cook on 5 November, took place under the theme "Digitalisation and AI Shaping the Future of Heating and Cooling". During her inaugural presidential address, Ms Cook highlighted the potential for AI to enhance system management and efficiency, while also addressing the need for greater industry understanding of both good and bad practices associated with these technologies.
The event drew attention to the need for improved skills and knowledge as foundational pillars to effectively harness the benefits of AI in managing cooling systems. Ms Cook emphasised the importance of preparedness amongst building engineers to make safe and informed decisions regarding data use. She posited the long-term advantages of AI, stating, “it’s going to help the engineers as they will be able to log on to a system and potentially diagnose what the issue is to help them prepare for a site.”
Despite the broadly optimistic outlook, audience members expressed concerns about the implications of increased automation for the human workforce. Public fears often echo themes from science fiction, speculating on the possibilities of sentient machines overshadowing human expertise. Addressing these concerns, Ms Cook clarified that AI serves as an augmentation tool rather than a replacement for skilled engineers. She asserted, “We are never not going to need those practical, hands-on skills,” advocating instead for a balance and integration of practical skills with AI capabilities.
The discussion also ventured into the practical applications of AI in providing predictive maintenance for refrigeration, air conditioning, and heat pump (RACHP) systems. Recent decades have already seen the utilisation of digital technologies for such purposes, with AI standing as the next step in this evolving landscape. Attendees queried the potential of AI in expanding access to predictive maintenance and the barriers to its adoption, such as the prevailing costs and the requirement for a comprehensive understanding of its implementation.
Cost emerged as a significant hindrance to AI adoption, not only regarding initial investment but also in evaluating the technology's long-term value against its setup costs. Effective deployment of AI necessitates robust data inputs for machine learning processes to ensure decisions on efficiency, occupant needs, and safety are well-informed.
Concerns regarding the environmental impact of AI also surfaced. Members questioned the energy demands required for AI and machine learning systems, especially given the carbon emissions from running data centres necessary for AI functionalities. There was speculation about the environmental costs of 'frivolous AI use', with Ms Cook mentioning ongoing studies on the energy and resource impact of digital actions like sending an email. She stressed the importance of transparent data to facilitate informed choices about the environmental footprint of AI-enhanced services within the industry.
Ms Cook concluded with a call for greater transparency and informed decision-making concerning AI’s environmental impacts, underlining that, “there is so much data we can gather and present to our customers to make more informed choices.”
The event highlighted both the potential advantages and the challenges of integrating AI into the cooling sector, advocating a carefully considered approach to ensure both human and environmental factors are appropriately balanced.
Source: Noah Wire Services