HVAC systems and lighting typically consume most of the electricity in buildings. HVAC equipment represents approximately 40%-60% of a building’s total energy consumption. The new sustainability goals of the Climate Agreement direct the focus to regulate these systems more efficiently and reducing their overall energy consumption. With the help of IoT, this can be done effortlessly.
Putting IoT to good use in HVAC systems
HVAC systems have been using smart sensors to control and automate the indoor climate for decades. These systems have already proven that they can improve the user experience, reduce maintenance costs, maximize comfort, and reduce energy consumption. IoT makes it possible to apply even more complex algorithms and collect, combine, and analyze data from multiple sources. Advances in artificial intelligence and the introduction of new mobile telecom networks complement IoT and make data collection and processing easier than ever before. The management of these systems will continue to improve as the implementation of IoT technology expands with new features, at a lower cost.
Reducing energy consumption
Housing associations and building managers are increasingly interested in real-time insights into the indoor climate from smart thermostats to sensors that monitor environmental changes.
According to a report from Zion Market Research, the global market for smart HVAC controls is expected to reach nearly $28.3 billion by 2025, compared to $8.3 billion in 2018. Sustainability is a key driver for implementing IoT in HVAC systems, as several of the key benefits – such as lowering energy needs and expanding equipment lifespan – improve sustainability simultaneously.
IoT sensors continuously collect data, such as temperature, airflow, and humidity, in addition to monitoring external factors. The data collected with these sensors can be combined with other relevant data, such as weather forecasts. By analyzing this data, it is possible to implement smart cooling and lighting strategies that can autonomously control the building’s conditions depending on the time of day or to meet the demand and use of space.
Temperature settings can also be automated with self-learning algorithms that keep optimizing the energy performance of the building – delivering an optimal experience to the users of the building at minimum energy consumption. Occupancy patterns, outdoor conditions, and the characteristics of the building itself all factor into this optimization.
Predictive Maintenance of HVAC Systems
Maintenance plans typically include site visits which are often scheduled at routine intervals, without considering the actual needs of the system. By connecting IoT sensors to the HVAC system and allowing data to communicate to a dashboard, patterns and trends are identified that can assist in predictive maintenance. An example of this is recognizing patterns that precede a malfunction. With the data from the sensors, corrective measures can be taken immediately to prevent the system from breaking down. This technique can be applied to the need for specific maintenance actions. By including the maintenance requirements in prediction algorithms, the maintenance program can switch from preventive to predictive. This shift can drastically reduce the number of inspection visits to each building, saving time, money, and energy.
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