The Role of IoT Monitoring and Satellite Data in Environmental Protection.

Modern global challenges—climate change, ecosystem degradation, deterioration of atmospheric air quality and water resources, loss of biodiversity, and increasing anthropogenic pressure—are shaping a new paradigm of environmental governance. According to the Intergovernmental Panel on Climate Change (IPCC), anthropogenic impacts have already led to a sustained increase in global temperatures, a rise in the frequency of extreme weather events, and changes in hydrological regimes in many regions of the world (IPCC, 2023). At the same time, the World Health Organization (WHO) notes that air pollution causes millions of premature deaths each year (WHO, 2022), while the United Nations Environment Programme (UNEP) records an accelerated rate of biodiversity loss (UNEP, 2023).

Under these conditions, traditional methods of environmental control—episodic laboratory analyses, fragmented field surveys, and static reporting models—are insufficient. They do not provide the timeliness, spatial completeness, or continuity of observations required for prompt responses to environmental risks. The modern environmental protection system requires a transition to digital, automated, and integrated monitoring tools capable of operating in real time and enabling decision-making based on big data.

Among the key technologies transforming environmental monitoring, a special place is occupied by the Internet of Things (Internet of Things, IoT) and satellite data from Earth remote sensing (Remote Sensing, RS).

IoT represents a network of intelligent sensors and devices deployed in natural and urbanized environments that continuously record environmental parameters—concentrations of pollutants, temperature, humidity, water levels, noise exposure, and other indicators. Data transmission is carried out via wireless networks (NB-IoT, LoRaWAN, GSM, 5G) to cloud platforms, where the data are analyzed using machine learning algorithms and predictive models.

Satellite remote sensing, in turn, provides global spatial coverage and regular updates of information on the state of the atmosphere, water bodies, soils, forest areas, and glaciers. Earth observation programs, such as the continuous Earth monitoring program within the European Union’s Copernicus space program and missions of the National Aeronautics and Space Administration (NASA), make it possible to track long-term climate trends, land-use changes, desertification processes, and the spread of natural disasters.

The highest efficiency is demonstrated by the integration of IoT and satellite technologies. Ground-based sensors ensure high accuracy and local detail of measurements, while satellite data form a large-scale picture of ongoing changes. This combination creates a multi-level monitoring system—from a specific observation point to regional and global levels of analysis.

As a result, a new model of environmental governance is formed, based on:

— continuity of observations;

— responsiveness;

— high spatiotemporal resolution of data;

— integration of large volumes of information into unified analytical platforms;

— the ability to forecast environmental risks.

The digitalization of environmental monitoring through IoT and satellite data is becoming not merely a technological trend, but a necessary condition for sustainable development, ensuring environmental safety, and efficient natural resource management in the 21st century.

1. Internet of Things (IoT) in Environmental Monitoring

The Internet of Things (IoT) is a distributed network of intelligent sensors, measurement modules, communication devices, and software integrated for data exchange and analytical processing in real time. In the environmental context, IoT systems enable continuous data collection on environmental conditions across large territories, automate measurement processes, and support timely decision-making.

1.1. Main Areas of IoT Application in Environmental Monitoring

Air Quality Monitoring. IoT air quality sensors record concentrations of key pollutants—fine particulate matter with a diameter of less than 2.5 microns (PM2.5), particulate matter with a diameter of 10 micrometers or less, including smoke, dust, soot, salts, acids, and metals (PM10), nitrogen dioxide (NO₂), carbon monoxide (CO), the allotropic triatomic form of oxygen (O₃), and sulfur dioxide (SO₂)—and transmit the data to servers for analysis. Such systems are used in cities for real-time pollution assessment and public warning.

Water Quality Monitoring. IoT devices can measure the acidity level of aqueous solutions (pH), concentrations of dissolved oxygen, turbidity, temperature, and other parameters in surface and groundwater. This is particularly important for monitoring drinking water sources, rivers, lakes, and treatment facilities.

Assessment of Soil Health and Agricultural Parameters. IoT soil sensors measure moisture, temperature, electrical conductivity, and nutrient concentrations. The collected data help optimize irrigation regimes, reduce fertilizer consumption, increase crop yields, and lower environmental pressure.

Monitoring of Noise Pollution and Other Urban Environmental Parameters. IoT devices are also used to measure noise levels, vibration, temperature, and humidity, as well as to monitor biological or chemical threats. These data contribute to improving the environmental conditions in cities and optimizing transport and infrastructure.

1.2. Advantages of IoT Systems in Environmental Applications

One of the key advantages of IoT systems in environmental monitoring is the continuity of data collection: sensors operate around the clock (24/7), ensuring a stable and systematic flow of information on the state of the environment. Unlike traditional one-time measurements, such systems generate dynamic time series, enabling the tracking of changes in indicators over the long term and the identification of trends.

IoT systems are characterized by a high degree of decentralization. The deployment of distributed sensor networks makes it possible to cover extensive areas—from individual industrial facilities to entire cities and regions—while simultaneously obtaining detailed local measurements. Such spatial flexibility is particularly important for monitoring heterogeneous environments, where environmental indicators may vary significantly even over short distances.

An additional advantage is the ability to integrate analytical tools and artificial intelligence algorithms. The collected data can be processed using machine learning methods and big data analytics (Big Data), which allows not only the recording of current indicators but also the development of predictive models, identification of hidden patterns, and assessment of the probability of environmental risks. As a result, IoT monitoring evolves from simple parameter recording into an intelligent environmental management system based on predictive analytics and scientifically grounded response scenarios.

1.3. Practical Example of IoT Application in Industrial Environmental Monitoring

The practical application of IoT technologies is particularly widespread in the industrial sector, where continuous control of pollutant emissions and discharges is required. In the energy, chemical, metallurgical, and oil and gas industries, automated continuous environmental monitoring systems (Continuous Monitoring Systems) are deployed, including gas concentration sensors, flow meters, pH analyzers, turbidity analyzers, temperature sensors, and other measurement devices.

Example 1. Continuous Emissions Monitoring (CEMS) — USA.

In the United States, Continuous Emissions Monitoring Systems (CEMS) are widely used. These systems automatically measure concentrations of sulfur dioxide (SO₂), nitrogen oxides (NOₓ), carbon dioxide (CO₂), particulate matter, and other pollutants in flue gases. Data are transmitted in real time to regulatory authorities and are used to verify compliance with environmental standards.

How the system works:

— sensors are installed directly in smokestacks;

— measurements are carried out continuously;

— data are automatically transmitted to a digital reporting system;

— alerts are generated when maximum permissible concentrations are exceeded.

This enables:

— early detection of technological failures;

— prevention of prolonged exceedances of emission limits;

— ensuring transparency of environmental reporting;

— minimization of penalties and reputational risks.

Example 2. Monitoring of Industrial Discharges under the EU Directive.

In the European Union, enterprises are required to implement automated monitoring systems in accordance with the Industrial Emissions Directive No. 2010/75 (Industrial Emissions Directive, IED). Such systems include IoT sensors for monitoring emissions into the atmosphere and discharges into water bodies.

Monitoring systems provide:

— continuous control of pollutant concentrations;

— storage and transmission of data in digital format;

— integration with governmental information platforms.

As a result, enterprises are required not only to record indicators but also to demonstrate compliance with regulatory standards based on objective digital data.

Example 3. IoT-Based Water Quality Monitoring — USA (USGS, National Real-Time Water Quality).

In the United States, the U.S. Geological Survey (USGS) maintains a network of stations for continuous and near real-time water quality monitoring. These stations are equipped with multiparameter sensors that regularly (at high frequency) measure pH, water temperature, electrical conductivity, dissolved oxygen, turbidity, as well as a number of other indicators. Data are automatically transmitted to USGS systems and are available for operational water resource management, monitoring the safety of recreational areas, and supporting decision-making for water supply and regulation.

Such a system enables:

— early detection of water quality deterioration (through sharp anomalies in turbidity, oxygen depletion, changes in pH, etc.);

— rapid response to potential accidental discharges or pollution events (alerts, control sampling, restrictive measures);

— assessment of dynamics and trends (including seasonal variations and those related to precipitation/flood events);

— formation of an evidence base for reporting and water body management based on continuous data series.

IoT monitoring has become a fundamental tool for modern environmental control systems. It enhances the accuracy, timeliness, and scale of observations, and also provides a foundation for integration with analytical platforms, including Earth remote sensing (RS) data, thereby making environmental management more efficient and scientifically grounded.

2. Satellite Data for Global Observation

Satellite-based Earth remote sensing (RS) systems play a key role in shaping the modern system of global environmental monitoring. Unlike ground-based measurements, which are limited to specific observation points, satellites provide large-scale spatial coverage and regular updates of information, enabling the tracking of the dynamics of natural processes at regional and global scales. Due to the high frequency of observations and the advancement of sensor technologies, RS has become a primary source of data for analyzing climate change, ecosystem conditions, and natural resources.

One of the most significant international programs is the European Copernicus Programme, implemented with the participation of the European Space Agency (European Space Agency). Within the framework of the program, the Sentinel satellite series operates. For example, Sentinel-2 provides multispectral imaging of land surfaces with high spatial resolution, making it possible to analyze land-use changes, the condition of agricultural crops, soil degradation, and the dynamics of forest areas. Sentinel-2 data are widely used for calculating vegetation indices (NDVI) and detecting processes of deforestation and desertification.

The Sentinel-3 satellite is focused on monitoring oceans and the atmosphere: it provides information on sea and land surface temperature, wave height, chlorophyll concentration, and other parameters, which is important for analyzing climate change and the condition of marine ecosystems. The regularity of observations makes it possible to track coastal erosion, algal blooms, and the dynamics of coastal zones.

An important area of satellite monitoring is associated with measuring greenhouse gas concentrations. The Japanese satellite Ibuki (GOSAT) is designed for global measurement of atmospheric concentrations of carbon dioxide (CO₂) and methane (CH₄). Such data are critically important for assessing the anthropogenic contribution to climate change, verifying national emissions reports, and supporting international climate agreements.

In practice, satellite data are used to detect large-scale deforestation in tropical regions, monitor the condition of water resources and water levels, analyze drought and desertification, track forest fires and the consequences of floods, as well as assess the dynamics of glaciers and snow cover. Satellite archives make it possible to compare current indicators with historical data, forming a scientific basis for forecasting future changes.

3. Synergy of IoT and Satellite Data

Maximum effectiveness in environmental monitoring is achieved not through the isolated use of IoT or satellite-based Earth remote sensing (RS) systems, but through their integration into a unified digital platform. Satellite observations provide broad spatial coverage and detect large-scale environmental changes, while IoT sensors deliver high-precision local information in real time. Such a combination makes it possible to integrate the global context with detailed measurements.

For example, data from the European Union’s Copernicus Programme are widely used for monitoring fires, air quality, and land conditions. The Copernicus Atmosphere Monitoring Service (CAMS) provides satellite data on concentrations of atmospheric pollutants and aerosols.

In the field of forest fires, this synergy is particularly evident. Sentinel-3 and Terra (NASA) satellites detect thermal anomalies and fire hotspots over large areas, while local air quality sensors and meteorological stations record smoke concentrations and their impact on populated areas. NASA’s Fire Information for Resource Management System (FIRMS) mapping web platform provides near real-time data on fires.

Similarly, in the field of water resources, satellite data on algal blooms or water surface temperature (Sentinel-3, MODIS) can be correlated with measurements from IoT water quality sensors deployed in specific water bodies. This makes it possible to refine the scale of the problem and respond promptly to emerging threats.

Thus, the integration of IoT and satellite data forms multi-level predictive models that are used in natural resource management, urban planning, emergency prevention, and environmental regulation. The space-to-ground integration approach is actively supported by the European Space Agency.

IoT monitoring and satellite observations today serve as fundamental technological pillars of the modern environmental control system. The Internet of Things ensures high-precision, localized, and continuous recording of environmental parameters—air and water quality, soil conditions, noise levels, emission concentrations, and other indicators. Satellite Earth remote sensing systems, in turn, provide a spatially extensive and temporally comparable picture of ongoing changes—from the regional level to the global level. This combination of detail and coverage makes it possible to move from fragmented observations to comprehensive environmental analysis.

The integration of ground-based IoT networks and satellite data creates a digital infrastructure capable of operating in real time. This implies not only the recording of the current state of the environment, but also the ability to identify trends, model development scenarios, and forecast potential risks. Through the use of machine learning algorithms and big data analytics, predictive models are formed that make it possible to assess in advance the probability of pollution events, natural disasters, or ecosystem degradation.

These technologies acquire particular importance in the context of climate change and increasing anthropogenic pressure. They provide an evidence base for the development of environmental policy, the improvement of regulatory mechanisms, and the control of compliance with environmental requirements. In addition, digital monitoring systems contribute to increasing the transparency of environmental information, thereby strengthening public oversight and trust in decision-making.

From a strategic perspective, the development of IoT and satellite observations forms the foundation for the creation of “smart” environmental platforms—digital twins of territories, integrated systems for water and forest resource management, and automated mechanisms for responding to emergency situations.

Thus, the synergy of space-based and ground-based technologies becomes a key instrument for the transition to sustainable natural resource management, reduction of environmental risks, and ensuring long-term environmental security.