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Artificial intelligence and response management: the basics

March 1, 2022


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Artificial intelligence (AI) has become both common and confusing as its role in our lives has grown exponentially in the last decade. The use of artificial intelligence in everything from transportation to healthcare has yielded countless benefits due to efficiency and reliability improvements. Examples include:      

  • In the transportation industry, AI is used to improve vehicle safety, reduce traffic congestion and predict delays in airline travel.
  • AI helps clinicians triage patients and prioritize treatment by evaluating scans, images and health records more reliably and quickly than healthcare workers.
  • AI has been instrumental in the global Covid response, from early warning systems to vaccine development.  

Across municipal and customer service industries,  AI is already trusted to:

  • Automate system control and monitoring, such as intelligent sewer network management
  • Predict required treatment changes based on weather or demand variations
  • Find the most efficient vehicle routes for scheduling service appointments

However, the basics of AI are still an enigma to many, and the use of it as a buzzword to describe something complicated or sophisticated has led to understandable misgivings about the technology.

AI and machine learning are often used interchangeably, but there are differences.

Artificial intelligence is a computer/technology that mimics human behavior by recognizing patterns and gaining insights based on instructional algorithms. It offers the ability to analyze and interpret large quantities of information much more accurately and efficiently than a human or even a team of humans.

An algorithm is a set of rules used by a computer or application to complete a task. In the case of Daupler AI, the algorithm is following instructions on how to classify incoming data by type and severity of incident. These instructions also enable it to identify duplicate reports and larger events.

Machine learning is a type of AI in which a machine automatically learns from past data to solve complex problems or perform tasks based on the intelligence it gains. Daupler AI’s proprietary algorithm has learned how to classify different data from tens of thousands of records and millions of data points. As it receives more data, it becomes even more accurate.

AI technology is frequently part of a software system in which it integrates with other functions such as data collection or reporting. Daupler AI is integrated into the Daupler’s response management software, Daupler RMS, to help automate the data input and evaluation process. This ensures response teams are equipped with the best available information as quickly as possible.

With the processing power of Daupler AI, our RMS software empowers organizations to handle incidents of all types and sizes with efficiency and precision. Learn how Daupler RMS can help to improve safety, customer service and system performance outcomes at daupler.com/demo.

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