The Internet of Things (IoT) revolution is in full swing, and with it comes an increasing amount of sensors that enable the collection of huge volumes of data.
However, it’s hard to make sense of all this data – lots of companies are still struggling to turn their IoT data into actionable insights. A new generation of AI-driven technologies is now emerging as a promising solution – these systems can understand, make sense of and learn from IoT data.
Another technology that is getting a major boost from IoT is artificial intelligence (AI). In the same way that data from sensors can monitor CO2 emissions in real-time or identify high-risk areas, AI algorithms can help reduce energy consumption by optimizing heating and cooling systems.
This could eventually allow for better distribution across cities – resulting in more efficient systems with a reduced need for new power plants. Read on to discover how AI and IoT together can prove to be the key to reducing the environmental impact of business operations.
The AI-IoT revolution is the key to a sustainable future, as it will allow for better data collection and analysis
The rise of sustainability managers is one of the most noticeable trends in corporate sustainability over the last few years.
They are now responsible for helping their organizations to identify and implement sustainable business solutions that can reduce costs and lift overall productivity. A large part of sustainability managers’ work is about identifying and reducing potential energy consumption and looking at ways to improve operational efficiency.
The sustainability revolution is hampered because sustainability managers still spend most of their time on data collection and analysis.
For instance, collecting data about energy consumption requires sustainability managers to carry out manual audits with handheld devices – it’s time-consuming, costly, and often inaccurate.
Furthermore, lots of sustainability professionals lack the necessary skills and knowledge to analyze this data.
IoT technology has become more advanced in recent years, so it’s easier than ever to collect data and create sustainable technology solutions. Although AI is not yet at the same level as IoT technology, it can help you advance your sustainable development goals faster by allowing machines to learn from data rather than humans.
The IoT revolution is providing sustainability managers with an arsenal of new tools and technology for sustainable development to help them do their jobs more effectively, including:
- Sensors that can collect accurate data on energy consumption, waste generation, and other sustainability performance metrics;
- Data processing software that turns this raw historic data into actionable insights;
- AI algorithms can help sustainability managers understand, interpret and act upon the data they collect.
Data from IoT devices can be used to monitor CO2 emissions in real time or identify high-risk areas
The Internet of Things (IoT) is rapidly becoming one of the most useful technologies for sustainability managers.
Every day, there are more and more sensors that measure sustainability performance. For instance, the carbon dioxide (CO2) levels in a factory can be measured by stationary CO2 sensors.
These IoT sensors are now being installed in many different parts of the organization’s operations – on vehicles, for example. So, sustainability managers can obtain useful sustainability insight from a large amount of data collected in real-time.
However, the sheer volume of sustainability-related data collected by IoT sensors is far too much for sustainability managers to handle manually or use in spreadsheets. The challenge is turning this big data into actionable insights – but with the help of AI-driven technologies, sustainability managers can do this on time.
For example, sustainability managers can use the Internet of Things to count the number of journeys made by company vehicles automatically. These journey counts can be used to calculate fuel consumption rates – which are one of the main drivers behind most sustainability initiatives.
Furthermore, sustainability managers can make more informed decisions about implementing their sustainability management system (SMS) by using sustainability data to identify high-risk areas and measure improvement more accurately.
AI algorithms can help reduce energy consumption by optimizing heating and cooling systems
With the rise of sustainability, managers have come to focus on reducing environmental impact through operational efficiency. One area that sustainability managers are looking at is vehicle fleets, as they can significantly impact sustainability through fuel consumption and carbon emissions.
In the past few years, sustainability managers have been able to get more from their vehicle fleets by implementing automated technology – including automated pay-as-you-go car-sharing schemes, where employees can use self-drive vehicles without owning them.
However, a new area that sustainability managers have been able to tap into is sustainability through increased energy efficiency.
With the help of advanced sustainable technology solutions, managers can use automation and advanced algorithms to optimize their heating and cooling systems. The precise control that AI allows organizations to monitor their facilities 24/7 using real-time data from IoT sensors, such as MicroSensor products.
This makes it easier for sustainability managers to detect patterns that lead to inefficiencies and then fix or avoid them.
Computer-based algorithms can be used to monitor energy consumption by taking readings from IoT sensors throughout the facility. This data is fed into an AI system, which analyzes it against past usage so sustainability managers can spot any anomalies or opportunities for saving on costs.
Smart grids could provide more efficient distribution of power across cities, reducing the need for new power plants
Another area sustainability managers have been able to use technology is in smart grid management – a system that monitors and manages the flow of electricity as it moves from transmission networks through to substations, where it can be used locally.
With the help of IoT sensors, sustainability managers can monitor energy usage patterns to spot patterns that might lead to blackouts (such as fluctuations in demand or environmental factors like weather).
With this data, sustainability managers can predict how much power their cities will need and ensure there is enough available at all times.
There are also opportunities for sustainability managers to introduce sustainability solutions into smart grids.
For example, sustainability managers could supply solar panels to residents to reduce the strain on a city’s power grid during times of peak demand – for instance, when workers return home from work at the end of a sunny day.
By using data from IoT sensors and Artificial Intelligence technology, sustainability managers can then ensure just the right amount of power available during these peak times.
Conclusion
The Internet of Things and Artificial Intelligence have become key components in sustainability initiatives worldwide.
Through collecting data from IoT sensors, sustainability managers can monitor greenhouse gas emissions in real-time, optimize heating and cooling systems, reduce energy consumption through smart grids, and streamline sustainability initiatives for maximum impact.