Page 210 - AI for Good-Innovate for Impact Final Report 2024
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AI for Good-Innovate for Impact



                      Use case – 49: AI-enabled Soil Analysis and Weather Station for

                      Local Farmers












                      Country: Ghana 

                      Organization: CSIR - Institute for Scientific and Technological Information 

                      Contact         person:        Dennis        Agyemanh           Nana        Gookyi
                      dennisgookyi@ gmail .com, +233503493435,
                                                    Fortunatus Aabangbio Wulnye fortunatuswulnye@ outlook .com ,
                                                    Roger Kwao Ahiadormey rogerkwao@ gmail .com
                                                    Michael Wilson yboabengwilson@ gmail .com
                                                    Yaw Twum Barimah ytbarimah@ yahoo .com
                                                    Paul Danquah pauldanquah@ yahoo .com


                      49�1� Use case summary table


                       Domain                 Agriculture
                       The problem to be      Inaccurate weather and soil condition predictions for local farm-
                       addressed              lands due to reliance on national meteorological data that is not
                                              specific to local areas. This leads to crop losses and reduced yield
                                              for local farmers.

                       Key aspects of the solu-  •  Real-time data collection using AI-enabled weather stations
                       tion                      and soil analysis sensors.
                                              •  Monitoring of rainfall intensity, wind intensity and direction,
                                                 temperature, humidity, pressure, and air quality.
                                              •  Soil analysis for temperature, humidity, pH, NPK, and conduc-
                                                 tivity (EC).
                                              •  Data visualization on dashboards and accessibility through
                                                 smartphone applications and web browsers.
                                              •  Predictive modeling for accurate local farm-specific forecasts.

                       Technology keywords    AI, soil analysis, weather station, real-time data, predictive model-
                                              ing, IoT, sensors
                       Data availability      Privately available

                       Metadata (type of data)   •  Environmental data (rainfall, wind, temperature, humidity, pres-
                                                 sure, air quality)
                                              •  Soil data (temperature, humidity, pH, NPK, conductivity)

                       Model Training and     Using collected data over time to design and refine predictive
                       fine-tuning            models for accurate local forecasts.

                       Testbeds or pilot deploy- https:// github .com/ ITU -AI -ML -in -5G -Challenge/ ITU -2024
                       ments                  -GenStorm -Submission -Next -Gen -TinyML -Smart -Weather -Station





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