Manish Kumar, EVP of digital energy, Schneider Electric looks at making schools smart.

When we think about education, we often focus on the curriculum, teaching methods, and even the quality of the teachers. But there’s another factor that can significantly impact student performance: the environment in which students learn. In the past, the school building itself may have seemed like a static, unchangeable backdrop. However, with today’s advancements in technology, we now have the ability to create dynamic, agile learning environments. These flexible spaces can be tailored to better meet the need of students, underscoring the fact that the physical environment plays a crucial role in shaping learning outcomes.

As the world grows hotter and more unpredictable due to climate change, it’s clear that the way we design our schools matters more than ever. Extreme temperatures, both hot and cold, can hinder students’ cognitive function, and in some cases, even prevent them from attending school. It’s not just about comfort; it’s about creating spaces that actively support the well-being and academic performance of students.

The good news is that we now have the tools and technology to create smarter, more efficient school buildings. And the most exciting part? Artificial intelligence (AI) and machine learning (ML) are playing a huge role in transforming these spaces, making them more sustainable, energy-efficient, and conducive to learning.

Designing smarter, healthier school environments

In an ideal world, every classroom would be perfectly lit, always at the ideal temperature, and free from distractions like noise or poor air quality. But in reality, this isn’t always the case. Schools are often underfunded, and many buildings are old or designed without the benefit of today’s technology.

However, with the rise of Internet of Things (IoT) devices and cloud-based technologies, we now have the ability to improve the environment of our schools in real-time. These technologies can collect data on a building’s performance, monitor air quality, adjust lighting and temperature, and even automate energy-saving features - all in real-time.

In fact, the market for building-related IoT has grown 21% between 2019 and 2021, and analysts predict a 12% annual growth through 2027. This translates to 2.5 billion connected devices in commercial buildings alone, many of which are being implemented in educational environments to create smarter, more responsive spaces.

Here are just a few ways these technologies can enhance student performance:

Lighting that supports learning


Natural light is one of the most underrated factors when it comes to student focus and concentration. Research has shown that classrooms with ample natural light improve cognitive function and student engagement. AI-powered systems can adjust artificial lighting based on the time of day or weather, ensuring that students always have the ideal lighting for learning. Additionally, energy-efficient LED lighting can be integrated, cutting down on costs while improving performance.

Smart ventilation for healthier classrooms


Poor ventilation not only affects air quality but also temperature control, which can lead to distractions and discomfort in the classroom. AI and machine learning can help schools maintain a consistent, comfortable temperature while improving air quality by automating ventilation systems. Studies have shown that just improving air quality can boost standardised test performance by as much as 14%. In addition, these systems can reduce energy consumption by adjusting airflow based on occupancy and real-time air quality data.

AI for efficient heating and cooling no matter the season


Climate-related disruptions are becoming more frequent and severe. Whether it's sweltering summer heat or bone-chilling winter cold, students' ability to focus suffers when the classroom environment is extreme. AI can help optimise heating and cooling systems to maintain a comfortable temperature year-round, ensuring that students aren’t distracted by the environment. And because these systems are smarter, they only use energy when needed, helping schools save on long-term energy costs.

The power of data and automation

The World Economic Forum estimates that digital technologies, like AI and ML, could account for a fifth of the emissions reductions needed to meet global net-zero targets by 2050. And while that’s a long-term goal, the work starts now.

To demonstrate a real example, SISAB (Skolfastigheter i Stockholm AB), which manages most of the school buildings in Stockholm, faced several challenges: energy inefficiency, a complex building automation system, and an inability to harness the data being generated by its existing systems. By leveraging AI, specifically an AI-powered HVAC system, it was able to optimise the operation of its 624 buildings serving over 200,000 students and staff.

According to the Schneider Electric Sustainability Research Institute's report, AI-Powered HVAC in Educational Buildings: A Net Digital Impact Use Case, the results were remarkable. Over just two winter seasons, SISAB achieved:

  • 15% savings in electricity costs
  • A 205-tonne reduction in greenhouse gas emissions
  • 4% savings in heating energy
  • 23% fewer complaints from building occupants
  • 8.93% reduction in total electricity consumption

The system showed a carbon cost-benefit ratio of 1:60, meaning for every unit of carbon used, 60 units of carbon were saved each year. From 2019 to 2023, AI integration helped reduce total carbon emissions by 259.17 tonnes. This includes 109.87 tons from district heating and 149.30 tonnes from electricity.

We also saw that the AI system integrated seamlessly with existing Building Management Systems (BMS), requiring minimal infrastructure changes and keeping costs low while minimising disruptions. The HVAC also provided more responsive heating and cooling, adjusting in real-time based on occupancy and other data.

The system paid for itself in just two years, showing how energy savings can fund sustainability improvements and, over time, allow for reinvestment into the learning environment. By recognising patterns in building occupancy, the system intelligently adjusted heating based on the presence of students and staff, reducing unnecessary energy consumption during low-occupancy periods, and creating a comfortable space where students could thrive.

What’s next?

The integration of AI and energy-efficient technologies in school buildings isn’t just about saving money, rather it’s about creating spaces that help students thrive. It’s about recognising that the environment plays a critical role in learning and making the most of the tools available to improve that environment.

By leveraging AI, machine learning, and energy-efficient solutions, we can create educational environments that are not only healthier and more comfortable but also more resilient, sustainable, and cost-effective for the future.

With smarter, more sustainable schools, we’re setting students up for success, not just in the classroom, but in their future lives and careers.