Earth’s temperatures continue to rise, and so do the stakes for environmental scientists and leaders. It’s time to upgrade our arsenal of tools to better understand and respond to environmental changes.
Given the prevalence of smart devices in our daily lives, it should come as no surprise that Internet of Things (IoT) technology is bringing some drastic upgrades to the way environmental data is collected, analyzed, and used for strategic decision-making. Especially in the face of a changing climate, the timing couldn’t be better for the rapid growth that IoT is experiencing.
The global IoT sensors market was worth approximately $8.5 billion in 2021. By 2028, it’s expected to grow to about $27.9 billion. IoT technology is here to stay, and sensors will likely continue to decrease in size and cost.
At the same time, connectivity networks are getting bigger and better. 5G provides robust support that allows for significantly larger amounts of data to be sent at significantly faster speeds. The benefits are so great that “ 5G…is forecast to cover about 75 percent of the world’s population in 2027.”
IoT technology might not seem like an obvious tool for combating climate change, but emerging trends are painting an encouraging picture.
Here are Three Ways IoT is Poised to Improve Environmental Monitoring:
#1: IoT-enabled Real-Time Alert Systems Will Reduce Severity and Scale of Impacts from Natural Disasters
Natural disasters such as wildfires, storms, and floods pose a dire threat to human life and ecosystems. They’re a clear impact of climate change. Quick response to these events can drastically reduce the negative impacts on ecosystems and human life. IoT-enabled forests and waterways, or “Smart Forests,” can help us avoid severe or large-scale impacts on the ecosystem through faster detection and response times.
One of the most promising functions of an IoT-enabled “smart forest” is advanced fire detection and response. A new fire could be instantaneously detected, even in complete darkness or before the fire would be visible to the naked eye. It would then trigger an immediate alert, giving the exact fire start location. AI and machine learning could also be incorporated to vastly improve predictability.
This is exactly what Vodafone has set out to do in Greece. They recently announced the creation of Greece’s first “Smart Forest” in the National Park of Parnitha. The system will utilize a combination of IoT sensors, Vodafone’s network, AI, and cameras. It will be able to instantly sense a fire based on increasing heat and camera-detected point of smoke. Fire authorities will be instantly alerted with exact coordinates and an image.
#2: Faster Turn-Around Time for Data Interpretation Will Help Us Respond to Changing Conditions in Real-Time
Traditional monitoring methods are time-consuming: a field technician needs to collect, transfer, and analyze the data. IoT is changing that by increasing the speed with which data is gathered and interpreted. It can provide a continuous stream of real-time information.
One of the clearest and most prevalent examples is the use of IoT to create more efficient and sustainable practices in agriculture. With an increasing population to feed and diminishing growing conditions due to climate change, farmers need data that is quickly available and clearly actionable. IoT systems can decrease wasteful irrigation as well as reliance on harmful pesticides and fertilizers. In fact, agriculture is the fastest growing sector within the IoT market, according to a report by Fortune Business Insights.
“Precision farming” utilizes in-field sensors to constantly monitor conditions such as soil moisture, light, temperature, growth rate, nutrient levels, humidity, etc. This information helps the farmer make rapid, data-driven decisions about planting, irrigation, and harvesting. Water is an especially critical resource that can be managed more efficiently with “smart irrigation” systems.
For example, one avocado farmer in Southern California was able to slash his water consumption by 75% in the midst of a multi-year drought. In an interview with Envirotec Magazine, Kurt Bantle explained how his “smart farming” experiment worked: “The soil moisture sensors let me drastically reduce water usage by telling me when to water and how deep to water to push the salts past the bulk of the rooting zone.”
#3: Better Data at Flexible Scales Will Allow for New Insights on Critical Resources
Some of our most critical resources are located within vast, remote, or highly complex areas. Human-based data collection methods can be significantly limited in terms of access, frequency, and parameters. Using sensors instead can have some serious advantages.
IoT sensors are flexible in size, cost, and function. Customized sensors can be placed at varying scales throughout vast landscapes. And they can be designed to collect a robust amount and quality of data that isn’t possible via manual collection methods. Real-time streams of data from remote or critical resources can provide us with new and valuable insights.
A recent collaboration between IBM and The Nature Conservancy India highlights this idea. They’ve implemented an IoT-based water quality monitoring system to help monitor and support the conservation of Lake Sembakkam, one of India’s most polluted lakes. IBM reported that “an estimated three months of IoT data would enable simple models already able to help The Nature Conservancy India to better understand water quality dynamics and spatial distributions in lakes that discrete data collections or monitoring cannot reveal.”
IoT Systems Are the Best Tools Available to Understand and Respond to Our Changing Environment
In the race against a changing climate, we need to leverage the power of the best technology available to understand and react to our environment. Now is the time for environmental leadership to explore ways IoT can vastly improve upon traditional methods that are costly, time-consuming, and simply not as capable.
The implications of IoT for environmental monitoring are massive: as sensors become more ubiquitous and our network systems more robust, we’ll be able to receive a constant stream of real-time data that will help decision-makers act swiftly. Early alert and detection systems can be combined with AI and machine learning to avert and reduce the negative impacts of climate change-fueled natural disasters.
This is an original piece of work from Natalya Apostolou, B2B writer. Find Natalya on LinkedIn.