A new age of automation is becoming part of our society today, the so-called Industry 4.0. Which is not only revolutionizing industrial processes and production sectors, but also aspects of everyday life.
These new automation advances have been possible through advances in the Internet of Things (IoT), which have allowed for more accurate manipulation of big data, identification of trends and remote access to data. This article looks at how these advanced data approaches contribute to making a building automated.
As various types of industry head towards the next industrial revolution, we can see the effects in some aspects of everyday life – especially within automated buildings that will ultimately lead to the development of “smart” cities.
Automation within buildings can take many forms, from the operation of various aspects of a building such as lifts and doors, to predictive and preventative maintenance and regulating the internal conditions and environment within a building – all without the need for an operator, unless they are alerted to an issue, or pre-emptively to a potential issue.
The Internet of Things (IoT) has brought about huge advances in building automation. The IoT combines a physical data sensing and transfer network with state-of-the-art data analysis, cloud computing and machine learning methods; which enables everything within a building to be interconnected, analyzed and run without the need of an operator, and act as an advanced alert protocol for any potential issues within a building.
It is a highly advanced data transfer network that requires minimal input, and when input is required, it can be from any remote location that has access to the internet.
Automating a Building Using IoT
Basic automation has been around in many parts of a building, such as using basic sensor relays to open doors. However, many parts of a building are now being exploited to not only function by themselves but now to run without any input from an operator apart from when the system predicts that downtime will be required.
It has particularly enabled buildings to run with minimal input and a minimal need to be on site (for example, if you are part of a maintenance team). Another key area where buildings have benefitted from automation is in the automatic regulation of the internal environment of the building.
Regulating Internal Conditions
There are many things that can affect the internal atmosphere of a building — fluctuations in temperature, particulate matter in the air resulting in lower air quality, humidity, etc.—most of which are governed by changes in external conditions such as the weather.
In some places, the weather can change quite frequently, and having someone on standby to change the temperature, relative humidity and other atmospheric factors in a building is a wasteful and laborious use of someone’s time.
By using IoT systems within buildings, the data can be regularly analyzed and continuously monitored through various sensors located at different points within a building. Pre-programming of the ideal conditions for each part (as each part of a building may have different condition requirements) enables the system to adjust the current environmental conditions to meet the ideal conditions.
This could be through heating, air conditioning, extra filtering of the air, or otherwise. Due to the fact that the system is interconnected, it can analyze data at all points and simultaneously adjust each room (or other defined locale) to meet their own tailored optimal conditions– something which a human would struggle to do. What’s more, this process can be done without the need of any personnel, thus making their time more meaningful and efficient.
In addition to automatically providing a much more comfortable atmosphere within the building, IoT systems can also help to reduce the energy consumption of a building. As well a monitoring the conditions that could make people uncomfortable, the sensor networks can determine who is using certain aspects of a building and turn off electrical devices accordingly.
For example, if a team leaves a meeting room and leaves the lights and a computer on, the system can detect this and turn them off, thus saving energy (as well as turning off other aspects that are no longer required such as heating or air-conditioning).
Additionally, because the internal conditions can be wholly dependent on the IoT system, heating and air-conditioning will be optimized to only be on until the desired temperature is reached, which will save energy from not being used unnecessarily.
If a person within the room was to switch either on, it would most likely be left on above (or below) the optimal temperature, which would then waste more energy. The system can also turn off any non-essential functions within the building to help minimize the energy usage.
Predictive and Preventative Maintenance
Many mechanical, electrical or functional aspects of a building are going to break down, malfunction or work less efficiently over time. Regardless of how well-designed these parts of the building are, there will be downtime.
Traditionally, this has meant that maintenance crews always need to be on-site in case something went down unexpectedly. That way, they could get to the affected site in the quickest time possible once something had broken down.
Integrating buildings with the IoT completely changes this dynamic, including how much time maintenance crews need to be physically present at the building itself. Through the IoT, various aspects of a building are monitored by a vast sensor network that measures various parameters of interest at specified times.
Moreover, it is the way that the system uses this data that is important. Previously, an operator would have to manually sift through this data to spot complex trends and anomalous results that could indicate when downtime and repairs might be needed for each part of the building. This now changes through IoT.
The IoT system will automatically analyze all the data from each sensor at each point of interest. This can be a huge amount of data, but advanced machine learning and data analysis techniques enable the system to automatically spot trends and identify anomalous results.
The system will also keep a record of all historical data, so if there is a certain trend for when downtime is likely to occur, the system will record it and then compare any future data against the recorded historical data to better predict equipment failings – and more importantly, spot the trend before the failings physically occur.
The data is both analyzed and reported in real-time. As the software develops itself to spot downtime and maintenance requirements ahead of the actual occurrence, there is not as much need for the maintenance team to be present all the time. IoT systems will often inform the operator and/or crew via text or email if downtime is imminent, meaning that they can then come in and fix the issue before it occurs without needing to be in the building the whole time.
IoT-based building automation brings about much greater efficiencies, faster maintenance response times and much-reduced downtimes, which benefits everybody who either works on, works in, or visits the building.