The Positive Impact of Data Mining:  
Environmental
The Positive Impact of Data Mining:   
Environmental
   

In the 5th Annual Survey (2011) data miners shared examples of situations where
data mining is having a positive impact on society.  
A summary of the top five
positive impact example topic areas is available.  Below is the full text of the
positive impact examples they shared in the topic area of the Environment:  


  • We are development model for:  -Predict the flow of rivers to meet two
    months before the availability of irrigation water and the potential for
    flooding and / or drought.  -Predict the occurrence of hail  from a  
    weather radar data.  -Predict crop yield and production from monthly
    variables surveyed in the field.  -Sort prevailing production systems to
    perform an economic analysis of production system and not for each
    particular activity.

  • Reduction of postharvest losses through better ability to call which lines
    of product to commit to which storage / distribution channels.

  • More than 90% of the chemicals on the market have not been tested on
    their potential hazards on humans and environment like
    carcinogenicity, developmental toxicity, mutagenicity, skin
    sensitization.  If they would be tested in traditional way, i.e., by animal
    testing, it would require more than 10 million additional animals, billions
    of euro, and more than 50 years in time.  Mathematical models (qsar
    models) obtained from observation data are going to help reducing,
    refining, and replacing animal tests in the near future.

  • It's very "green" ... targeting results in lower mail volumes.  It's very
    profitable ... it increases the bottom line.  It's good for customers ... they
    are more satisfied when properly implemented as part of a larger
    customer relationship strategy.

  • Data Mining makes better use of resources.  It also allows us to identify
    people in need of services.

  • Weather modeling, and the risk assessment of damage caused by
    environmental factors.

  • Better and proactive Risk management,  Economic forecast and
    improved agriculture output.

  • Clearly/empirically, (and *not* anecdotally), understanding how we are
    *actually* destroying our planet, and subsequently taking all
    appropriate/necessary actions to nurture our planet "back to health" --
    *not* motivated by or pursued for profit, politics, or any other form of
    unethical benefit.

  • Environment management.
Copyright (c) 2012 Rexer Analytics, All rights reserved