Bridging the Gap: How AI Enhances IoT

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At the core of IoT are physical objects – the “things” that consist of hardware with, for example, embedded sensors. Once connected to the Internet, IoT sensors provide data that can be a foundation for valuable insights about different processes. The device’s historical sensor data is stored in a database, a database that underpins a user-visible graphical interface. The diagrams and gauges are nice, but they can be challenging to understand for those without a technical background. One challenge is how we can make data from sensors more understandable and more actionable. After all, IoT data that can be shared with more users means that the data can be more accessible, and sharing is not just caring; it means that IoT data can be used by more people, resulting in more democratized systems.

The crossroads of super-powers
The emergence of AI and IoT marks a defining moment in technological evolution. In 2023, the synergy between AI’s data analysis capabilities and IoT’s expansive sensor networks opened the door to something new: AIoT. AIoT transforms how we interact with and interpret data. This convergence is not just a progression but a paradigm shift, setting new data utilization benchmarks for business innovation and individual empowerment. I was eager to explore this interesting field of development and had the fortune to work with a partner that could use our sensors’ generated data and combine IoT with AI to generate better insights. IoT sensors generate data, and AI analyzes it. But before delving into the experiment, let’s explore the background of my chosen focus area: building automation.

Energy efficiency in buildings: a real challenge
With the building industry accounting for a significant share of global energy consumption and greenhouse gas emissions, there’s an urgent call for efficient solutions. The EU’s target of a 55% reduction in emissions by 2030 underscores this necessity. This sector was the perfect playground for a test. Integrating IoT in the building sector, especially with AI’s analytical prowess, revolutionizes energy management. This synergy is pivotal in driving insightful data-led behavior changes and operational optimizations.

IoT and AI offer a dynamic approach, surpassing traditional energy-saving methods by providing a more nuanced, data-driven strategy for energy optimization.

AI: driving change for the better
AI’s integration elevates the functionality of IoT in building management, enabling predictive and adaptive control of systems like HVAC. This advanced interplay boosts energy efficiency and ensures compliance with regulatory standards for temperature and air quality, which are crucial for occupant health and comfort.

IoT’s role in gathering real-time data about indoor environments, paired with AI’s ability to analyze this information intelligently, is transforming the approach to building management. This combination benefits new constructions and existing infrastructures through retrofit IoT solutions, rejuvenating older buildings with modern efficiency standards.

Practical Implementation
Our Stockholm office exemplifies the practical benefits of IoT in building management. It is an old factory building. But recent upgrades in the heating and ventilation systems had the potential of generating a better indoor climate but the implementation seemed lacking. The temperature remains low both day and night. Could IoT sensors provide real-time insights into indoor conditions and suggest changes? Typically, such measurements are presented in complex diagrams. What if, instead, we could analyze the data to make it more comprehensible and provide actionable recommendations?

In collaboration with edge2cloud, we brought together these monumental technological breakthroughs. IoT sensors meticulously gather data, forming a digital representation of the physical world. AI then takes the reins, interpreting and presenting this data efficiently and understandably. The result? A web interface that not only displays familiar data and charts but also leverages AI to summarize data and automatically provide recommendations for improvements and adjustments.

Predictive analysis – a first leap
By leveraging machine learning to continuously analyze data from six straightforward measurement points—two indoor temperatures, three humidity measurement points, and an outdoor temperature sensor—we and our partners have created a platform. This platform not only analyzes current conditions but also anticipates future needs, offering suggestions for action. Imagine a system that not only alerts you to low humidity in the office but also proposes the optimal time to activate a humidifier without lifting a finger. Furthermore, it predicts future low humidity events and offers clear recommendations, much easier to grasp than interpreting charts alone.

Comprehensible Data
The test exemplifies how AI can analyze IoT data, making it comprehensible and yielding tangible results.

When AI analyzes a diagram and outputs this text, it is much easier to understand. For example:

· Temperature: Oscillating between 20°C and 22°C, with an average around 21°C
· Humidity: Fluctuating between 37% and 45%, averaging slightly above 40%

It is much easier to understand than two diagrams with a reading every five minutes the last 24 hours.

AI can also present insights

like this:

· Indoor temperatures slightly rise during daylight, potentially influenced by sunlight or building use.
· Outdoor temperatures significantly decrease at night, aligning with expectations.
· Indoor humidity maintains relative consistency between day and night.

Overcoming Challenges in Building Industry with AI and IoT
Despite its traditional resistance to change, the building industry faces unique challenges in adopting IoT and AI. Yet, the rewards are substantial, with significant energy savings and improved work environments. The key lies in implementing actionable, intelligent measures that provide immediate benefits and insights.

Envisioning an Intelligent Future with AI and IoT
As AI and IoT converge, they promise a future where technology transcends its tool-like existence to become an integral, intelligent partner in enhancing business operations and everyday life. This convergence heralds a new era of efficiency and sustainability, fundamentally reshaping building energy management and contributing to a more sustainable future.

The potential of AI and IoT extends well beyond building management. Their combined capabilities are poised to revolutionize various industries, setting new operational optimization and innovation standards.

Aligning Agenda 2030 Through AI and IoT
AI and IoT collaboration plays a crucial role in achieving the United Nations’ Agenda 2030 goals. These technologies align closely with global sustainability objectives by optimizing energy usage, promoting renewable energy sources, and enabling efficient urban planning, showcasing their potential to drive substantial positive change.

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