Pollution affects all life on Earth, whether it be from industrial carbon dioxide emissions, landfills, factory runoff, farms, or the myriad of industrial, commercial, and domestic sources. Real-time monitoring of pollution and the environment is crucial to identifying ecologically harmful substances and mitigating their effects on the environment and human health. This article will explore real-time pollution monitoring and its benefits for better environmental protection.
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Pollution: The Scale of the Problem
All life depends on a healthy environment, free of harmful materials. Pollution, which introduces harmful materials (pollutants) into the atmosphere, can threaten everything from single-celled organisms to humans, plants, and animals.
Pollutants come from natural sources, such as volcanic eruptions, or human activity. Almost all activities vital to modern industrialized society can release pollutants into the atmosphere, rivers, lakes, oceans, or land.
Urban areas are more polluted than rural areas due to increased industrial activity, domestic waste, and emissions from large road vehicles. However, pollution can spread to remote areas such as the middle of the ocean and the Antarctic ice sheet, making it a global issue that is incredibly hard to solve.1,2
Ocean and air currents can carry pollution far and wide. Marine animals can ingest microplastics, and factory smoke can end up in neighboring nations. Air pollution is one of the biggest killers globally, causes debilitating health conditions, and costs upward of several billion dollars a year to mitigate. The scale of the problem is vast and requires constant monitoring.
Types of Real-Time Monitoring Solutions
Scientists have developed several robust and innovative real-time environmental pollution monitoring solutions in the past few decades. Some of the main technologies employed in real-time monitoring are listed below.3
Real-time sensor networks
Sensor networks are becoming increasingly important for several industries and have started to play a prominent role in real-time environmental monitoring over recent years.
These dispersed networks monitor and record environmental systems, feeding them back to central data processing centers over an Internet connection via their own APIs or bespoke connections. Anomaly detection ensures that inaccurate data from potentially compromised sensors and devices is accounted for. Stream-based importers are an important part of these dispersed real-time networks.
Sensor observation services
A sensor observation service queries real-time sensor network data and time series, allowing interoperable management of sensor data streams. It is a web-based service that allows observations to be queried and provides metadata.
Analytics platforms
With these platforms, datasets from Geographic Information Systems (GIS) can be analyzed at scale in real time. They can also be ingested and queried on a granular level. Analysts can analyze and cross-reference vast datasets for real-time environmental monitoring by incorporating features such as interactive data visualizations.
Internet of Things (IoT) technologies and machine learning
IoT devices can transmit real-time environmental and pollution data to the cloud and other remote storage devices to monitor, analyze, and visualize datasets. Machine learning models and deep learning algorithms can interpret previously difficult-to-analyze data such as cloud wisps. While these technologies provide powerful capabilities beyond those of humans, there is still a need for human elements.
Telemetry systems
Telemetry systems can wirelessly transmit environmental data over cellular networks, satellites, or radio. These are highly appropriate for real-time monitoring of remote networks where other solutions may fall short.
Recent Developments in Real-Time Environmental Monitoring
Interest in real-time environmental monitoring has increased in recent years, and researchers have developed several innovative solutions.
Researchers from India have developed a real-time vehicle emissions tracking system utilizing cloud-enabled neural networks. The authors of the 2024 paper have noted that there are issues with current real-time data processing and scalability technologies. The authors have developed a potentially robust emissions monitoring solution using a distributed computing and cloud-based solution.4
Cloud-based systems are especially useful as they can handle vast amounts of real-time data due to their vastly improved storage over traditional computing solutions. This ensures the solution's scalability. The neural network model was trained on large vehicle emissions datasets, improving detection and tracking capabilities.
Generative AI models have emerged as highly disruptive technologies over the last few years. A paper has proposed using ChatGPT and Bard to improve water and air pollution monitoring strategies. The framework developed by the researchers could help address challenges centered around public real-time monitoring and public engagement and decision-making.5
This proposed generative AI-based solution incorporates technologies such as IoT, sensor networks, and satellite imagery to comprehensively understand pollution dynamics. The paper demonstrated how human elements and AI can be used in this complex field to analyze and act upon large volumes of data, although the authors have noted some ethical concerns with AI use.
Another recently published paper has demonstrated a system for real-time microplastic identification using polarization and spectroscopic holography, which offers benefits over conventional optical microscopy techniques.6 Finally, a recent Chinese research paper has featured an innovative approach to air pollution monitoring using breath-borne gaseous biomarkers from rats.7
In Summary
The damage done to the environment and human health by pollution from industrial activities has been well-known for a few decades. Over recent years, improving real-time environmental monitoring capabilities has been a central concern for several researchers and companies, leading to innovative solutions leveraging disruptive Industry 4.0 technologies such as sensors, AI, IoT, and machine learning.
If the UN’s sustainable development goals (SDGs) are to be met, pollution from sources such as factories, vehicle emissions, and plastics must be comprehensively and rapidly reduced. Significant investment in innovative real-time pollution and environmental monitoring solutions will likely be needed over the coming years to help achieve this.
References and Further Reading
- National Geographic (2024) Pollution [online] nationalgeographic.org. Available at: https://education.nationalgeographic.org/resource/pollution/ (Accessed on 21 June 2024)
- Marzouk, S (2017) 20 shocking facts about air pollution [online] Friends of the Earth. Available at: https://friendsoftheearth.uk/climate/20-shocking-facts-about-air-pollution (Accessed on 21 June 2024)
- Heavy.AI (2021) How Real-Time Environmental Monitoring Systems and Improving our Relationship with the Planet [online] Available at: https://www.heavy.ai/blog/how-real-time-environmental-monitoring-systems-are-improving-our-relationship-with-the-planet (Accessed on 21 June 2024)
- N. Anusha et al. (2024) Cloud-Enabled Neural Networks for Intelligent Vehicle Emissions Tracking and Analysis 2024 International Conference on Automation and Computation (AUTOCOM) pp. 232-236 [online] IEEE. Available at: https://ieeexplore.ieee.org/abstract/document/10486105 (Accessed on 21 June 2024)
- Rane, N, Choudhary., S & Rane, J (2024) Enhancing water and air pollution monitoring and control through ChatGPT and similar generative artificial intelligence implementation SSRN [online] Available at: https://dx.doi.org/10.2139/ssrn.4681733 (Accessed on 21 June 2024)
- Zhu, Y et al. (2024) Smart polarization and spectroscopic holography for real-time microplastics identification Nature Communications Engineering 3 Article No.: 32 [online] nature.com. Available at: https://www.nature.com/articles/s44172-024-00178-4 (Accessed on 21 June 2024)
- Zhu, C & Yao, M (2024) Real-Time Monitoring of Air Pollution Health Impacts Using Breath-Borne Gaseous Biomarkers from Rats Environ. Sci. Technol. 58:10 pp. 4522-4534 [online] ACS Publications. Available at: https://pubs.acs.org/doi/abs/10.1021/acs.est.3c08629 (Accessed on 21 June 2024)
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