Modern industrial sites are getting more and more connected. They have sensors to measure emissions, air quality, temperature, pressure, flow rate, and other environmental variables in real time.
But the mere collection of data from each sensor does not exhaust all possible benefits.
The true value lies in establishing connections between those sensors and an architecture of the Industrial Internet of Things (IIoT) that will collect, process, analyze, and visualize environmental data.
What is Industrial IoT?
Industrial IoT connects physical industrial equipment and sensors with digital systems.
Here is how an environmental monitoring architecture looks like:
Environmental Sensors
↓
IIoT Gateway
↓
Edge Processing
↓
Cloud / Data Platform
↓
Analytics & Dashboard
↓
Operator Action
Each of those layers participates in creating meaningful information out of raw measurements.
Connecting Multiple Sensors
In industrial environments, there may be multiple environmental parameters to monitor.
For example, the monitoring system may gather:
- Data on emissions
- Measurements of air quality
- Data on temperature
- Information on humidity
- Data on pressure
- Flow rate measurements
- Particulate data
Connecting these sources of data provides for a broader view of environmental conditions than independent analysis of separate measurements.
Why is Real-Time Monitoring Important?
Regular periodic measurements provide for some snapshots of environmental conditions.
Continuous real-time monitoring allows for creating a much deeper picture.
The continuous stream of data may be very helpful in identifying sudden changes, unusual readings, or emerging trends.
For instance, when some unexpected changes appear in emissions-related measurements, it becomes possible to raise an alarm in advance to investigate the situation.
The idea is not to automate all possible decisions but to give operators access to the data in a timely manner to make better-informed decisions.
The Role of Edge Computing
Sending data from all sensors directly to the cloud does not make sense in many cases.
The edge gateway will be able to process the information at a point close to its source and do such operations as filtering data, monitoring sensor status, aggregating readings, and raising local alarms.
It will help to save bandwidth and increase responsiveness of the system.
Cloud-based platforms will take care of storing all data, centralizing dashboards, historical analytics, and reporting.
Where the Role of AI Should Be Found
An additional analytics layer can be introduced by machine learning models in order to analyze historical and real-time data for possible patterns and anomalies.
The possible areas of usage are:
- Environmental anomalies
- Predictive maintenance
- Equipment diagnostics
- Emissions trends
- Optimization processes
However, AI shouldn't replace sensors and engineering knowledge in this area.
From Raw Measurements to Information
An IIoT monitoring system consists not only of sensors. However, the data obtained by these sensors should be:
Collected → Validated → Processed → Analyzed → Visualized → Action Taken
The process allows transforming raw measurements into information usable for operators.
The Challenges That Should Be Considered
There are certain challenges to take into account when building a monitoring system.
These are:
- Sensor accuracy
- Calibration
- Network stability
- Cybersecurity
- Data storage
- System integration
- Scalability
- Device maintenance
All of them should be taken into consideration in the architecture of the system.
The Future of Environmental Monitoring
Environmental monitoring becomes increasingly connected and based on the use of AI, edge computing, smart sensors, and IIoT platforms.
The future is not about sensors installation only but about building the system that will transform reliable environmental data into actionable insights.
This solution may help industries to increase their environmental visibility, respond faster and make more informed decisions in favor of sustainability.
To read more insights about Industrial IoT, emissions monitoring, AI, and environmental technologies check our website Emissions and Stack .
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