Organic plant material microbial test kit devices and processing method

An apparatus for testing organic plant materials, comprising:

• a plurality of machine-readable QR code identifiers positioned at multiple testing locations within a facility;
• a growth stimulator solution configured to create samples at the multiple testing locations to facilitate detection of contaminants;
• a portable incubator located at the testing location configured to heat the created samples to accelerate a microorganism growth within the samples;
• a plurality of sensors wirelessly coupled to a remote server configured to detect and analyze environmental conditions at the multiple testing locations;
• a camera configured to capture images of the microorganism growth within the samples, wherein the captured images and the environmental conditions are correlated to the associated machine-readable QR code identifiers and transmitted to a remote server;
• an artificial intelligence processor coupled to the remote server and configured to analyze and compare the captured images and the environmental data against known harmful microorganisms to identify microbial contamination based on the analysis and comparison using pattern recognition;
• wherein the artificial intelligence processor is further configured to use the identified microbial contamination to generate contamination reports including detected infestations and remediation recommendations with mitigation actions;
• a graphical user interface configured to display to a user the contamination reports and the recommendations;
• and
• wherein a facility map is generated and displayed on the graphical user interface with hotspot locations of the detected infestations of the contamination reports associated with the machine-readable QR code identifiers and wherein the artificial intelligence processor is further configured to create to predict contamination spread of the microorganism growth and generate remediation recommendations for preventative measures to prevent the contamination spread.

An apparatus for testing organic plant materials, comprising:

• a plurality of machine-readable QR code identifiers positioned at multiple testing locations within a facility;
• a growth stimulator solution configured to create samples at the multiple testing locations to facilitate detection of contaminants;
• a portable incubator located at the testing location configured to heat the created samples to accelerate a microorganism growth within the samples;
• a plurality of sensors wirelessly coupled to a remote server configured to detect and analyze environmental conditions at the multiple testing locations;
• a camera configured to capture images of the microorganism growth within the samples, wherein the captured images and the environmental conditions are correlated to the associated machine-readable QR code identifiers and transmitted to a remote server;
• an artificial intelligence processor coupled to the remote server and configured to analyze and compare the captured images and the environmental data against known harmful microorganisms to identify microbial contamination based on the analysis and comparison using pattern recognition;
• wherein the artificial intelligence processor is further configured to use the identified microbial contamination to generate contamination reports including detected infestations and remediation recommendations with mitigation actions;
• a graphical user interface configured to display to a user the contamination reports and the recommendations;
• wherein the artificial intelligence processor includes a voice module with voice commands configured to allow the user to communicate with the artificial intelligence processor to interactively receive information about the contamination reports with the detected infestations and remediation recommendations with mitigation actions;
• and
• wherein a facility map is generated and displayed on the graphical user interface with hotspot locations of the detected infestations of the contamination reports associated with the machine-readable QR code identifiers.