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AI is more than ChatGPT: How Hawa Dawa has been successfully integrating AI in the core of the air quality monitoring method

ChatGPT is really cool. Since it was launched to the public in November 2022, ordinary people from a wide variety of different areas have been testing it. They have played around with it and tried to determine how they can work with it in the most meaningful way. „ChatGPT is a conversational artificial intelligence model developed by OpenAI. It is trained on a large corpus of text data from the internet and has the ability to generate human-like text based on the input it receives“, ChatGPT explains itself.

So with ChatGPT, AI has become somehow more tangible for all of us. We can immediately see the result of the AI work and evaluate it. We understand: AI has arrived in our daily lives.

Hawa Dawa recognized the opportunities of AI for environmental monitoring from the very beginning. AI is – together with the advanced measurement device – the core of Hawa Dawa’s air monitoring method. The Hawa Dawa method leverages multiple advantages of AI, such as

  • Increased efficiency: AI algorithms can automate routine tasks, reducing the time and effort required to complete them.
  • Improved accuracy: AI systems can analyze large amounts of data and identify patterns and correlations that might go unnoticed by human experts.
  • Better decision-making: AI algorithms can help individuals and organizations make better decisions by providing insights and recommendations based on data analysis.
  • Data Cleaning: AI algorithms can identify and remove any errors, outliers, or irrelevant data points from the raw sensor readings, ensuring that only accurate and relevant data is used for further analysis.
  • Data Calibration: AI can be used to calibrate data readings that may be influenced by external factors such as changes in the environment or equipment degradation.
  • Sensor Fusion: AI can be used to combine data from multiple sensors to create a more comprehensive and accurate picture of the environment. This helps to overcome the limitations of individual sensors.
  • Modelling: AI algorithms can be trained on calibrated data to create and continuously refine models that can predict environmental parameters. These models can be used to analyze the data over time, identify trends, develop area-wide heatmaps based on single sensor readings, and make predictions about future environmental conditions.

Integrating AI into the product from the very beginning, Hawa Dawa has been able to move the complexity of reliable environmental monitoring from sophisticated hardware infrastructure to AI-based modelling. Among others, this approach provides the benefits of significant savings in cost and efforts for setup and maintenance, full scalability, and continuous improvements and enhancements for the product and existing implementations of the product.

The reliability and accuracy of the Hawa Dawa measurement method’s reliability and accuracy were confirmed by TÜV Süd and in multiple direct comparisons with various alternative solutions. If you want to learn more about this, you are invited to read „An AI Story“.