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The Digital Forest



The Internet of Things (IoT) is a rapidly growing field with applications in a wide range of industries. Early adopters were drawn to its potential for making homes more convenient and efficient, but recent developments have shown that IoT can also be used to improve healthcare, transportation, and manufacturing.

The IoT can be thought of as a network of physical objects – or things – that are embedded with sensors, software, and network connectivity to collect and exchange data. The data collected from IoT devices can be used to improve efficiency, productivity, and decision making in a variety of industries.

Advancements in sensor technology, cloud computing, wireless connectivity, and artificial intelligence have led to a rapid growth in the use of IoT. IoT devices are now being used in a wide range of applications, including healthcare, manufacturing, and fleet management.

For example, in the healthcare industry, IoT is being used to monitor patients remotely, track medical equipment, and improve patient care. Wearable devices can be used to collect data on patients’ vital signs, which can be sent to doctors for monitoring; this can help doctors identify potential problems early on and intervene before they become serious.

The Digital Forest

Another arena that’s benefitting from proliferating IoT use-cases is the forest. Forest health monitoring assesses and ensures the well-being of forest environments by evaluating various indicators such as tree growth, tree mortality, and outbreaks of pests and diseases. Before the emergence of disruptive IoT technologies, this work would primarily have been conducted manually, often by human observation and fieldwork.

However, deploying IoT sensors in the forest provides forestry owners and other stakeholders with valuable real-time data such as temperature, humidity, soil moisture, and air quality. This information can then be used to identify potential problems, such as drought, pests, or diseases.

Deploying Internet of Things sensors in the forest provides forestry owners and other stakeholders with valuable real-time data such as temperature, humidity, soil moisture, and air quality. Photo courtesy Dryad Networks.

While in-depth, qualitative research and monitoring will always have an important role to play, the digitization of forest health monitoring yields many benefits. Humanled efforts are very labor-intensive, time-consuming and face significant issues when it comes to covering and monitoring large forests – especially remote ones. There will also be a lag in data availability due to the data needing to be manually collated and interpreted.

IoT technology has revolutionized forest health monitoring by enabling real-time data collection, automated monitoring, and remote data transmission. Sensors placed in the forest can now provide continuous and up-to-date information on crucial parameters, allowing for rapid actionable insights and therefore greatly enhancing the effectiveness and efficiency of forest health monitoring practices.

Companies such as Ireland-based Treemetrics uses advanced technologies such as drones, remote sensing and IoT sensors to collect data on tree inventory, growth rates, and timber quality. In the United States, SilviaTerra combines remote sensing, machine learning, and IoT technologies to offer forest inventory and management services. Berlin-based Dryad Networks specializes in forest monitoring solutions using IoT sensors; its solarpowered sensor network collects real-time data on environmental factors such as temperature, humidity, soil moisture, and air quality. This data helps in assessing forest health and detecting potential risks.

A Pressing Problem

One of the most pressing and devastating risks that forests face is wildfires. Wildfires are a major source of greenhouse gas emissions, with some estimates claiming that they account for up to one-fifth of all emissions. When forests burn, they release carbon dioxide, methane, and other pollutants into the atmosphere. These gasses contribute to climate change, which in turn makes wildfires more likely and more severe.

As well as providing forest health monitoring insights via its IoT mesh network in the forest, Dryad’s initial focus is on wildfire detection. By monitoring environmental conditions within a forest, the system is able to – with the help of artificial intelligence – detect a smoldering fire. Because the environmental conditions change when a fire first starts, Dryad’s network of sensors is able to provide wildfire alerts within minutes, giving firefighters a crucial head start.

The Electronic Nose

Dryad’s system can be thought of as an electronic nose that’s finely attuned to the smell of the forest. When this smell deviates from what is expected, Dryad’s IoT network of sensors and gateways can check whether a smoldering fire is within the vicinity. If this is the case, an alert is sent across the mesh network to the end-user’s cloud platform, raising the alarm. Firefighters can then use this information to quickly locate the fire.


There are many benefits to leveraging IoT technologies when it comes to wildfires. While legacy approaches such as cameras and satellites will have a role to play, sensorbased solutions offer advantages when it comes to early detection.

Firstly, IoT sensors provide continuous and real-time monitoring of environmental conditions; this allows for immediate detection of changes in temperature, humidity, and smoke, enabling rapid response and early wildfire detection.

Secondly, deployment of sensors within the forest itself ensures rapid detection; this means wildfires can be detected at their early stages, even in remote or inaccessible locations, reducing response time and preventing fires from spreading.

Sensor-based approaches are often more cost-effective than relying solely on cameras or satellites. Cameras require infrastructure setup, maintenance, and have a limited field of view, while satellites can be expensive and have limitations in terms of coverage and frequency of imagery. In contrast, IoT sensors are relatively affordable, easy to deploy, and can cover a larger area.

Finally, sensor-based approaches allow for integration with advanced data analytics and other IoT tools. By combining sensor data with machine learning algorithms, the digital forest allows for advanced analysis, pattern recognition, and early warning system optimization, further enhancing the accuracy and effectiveness of wildfire detection.

The potential benefits of IoT are vast, and the technology is evolving. The future of wildland fire detection is being shaped by IoT and sensor technology, hopefully leading to a safer and more sustainable coexistence between humans and nature.

Ben Jones has held a series of marketing, PR and project management roles in biotech, agri-tech and the circular economy. During his time in the university sector in the UK before moving to Dryad Networks, he created and managed an accelerator programme for biotech and agri-tech startups. In his current role, Jones leads Dryad’s marketing and public relations efforts.