Algorithmic Imaging of All Matter obtained from Clusters and Single Data Points.
This new disclosure is based on detection of all types of matter that will assist in understanding how contaminates, pollutants, diseases and pathogens form in medical settings, in farming, greenhouse settings, as well as in our homes and the environment.
Matter described for purposes of the new disclosure is anything that takes up space and has weight. Matter can be bodily fluids, bacteria, viruses, dust, airborne liquid droplets, allergens, and smoke particles or any clusters thereof.
Biosensing is a data technology company that’s utilizes algorithms and quantum computing in the future to gather (using self directed drones and robots that utilize machine thinking), identify, and organize al types of matter data.
The autonomous Ai application gathers data, identifies and categorizes all types of data such as bodily fluids in medical settings.
Patents are pending worldwide.
The Biosensing AI matter database training application utilizes many new methods and applications to assist in the transfer of obtained data from matter detection apparatuses to identify, break apart clusters (if needed for accurate detection) and categorize the data with applied secure measures.
Biosensing has a sub application called Patient Data Private Investigator "AI Desa". The patient has 3 types of data- pre birth, post birth data, and ancillary environmental exposure data (patent pending). Pre birth data is all family historical data. The data is obtained by both the AI Desa ambient listening technology as well as the Private investigator "AI Desa PI" to scour all electronic data forms to compile data. Post Birth data is any data that can be obtained such as medical data and forecasting to alert the patient of possible sicknesses that may encounter. Environmental data is obtained by the AI Desa PI whereby the patient was or may have been exposed to toxins and or contaminates. Examples would be if the patient was living near a disaster such as the Palestine Train Derailment or the Flint Michigan water crisis.
Another component of the ABIS algorithms is the detection (utilizing the UMMDA) and elimination pathogens and disease spreading matter (utilizing biosurfactants) that may affect patients as well as medical staff.
There are 5 types of algorithms in the ABIS database, successful procedures, unsuccessful procedures, management of all facets of the ABIS database applications, forecasting algorithms of possible future events in the medical operating rooms, and error algorithms.
Robots and Drones scan for disease causing micro organisms before, during and after medical surgical procedures utilizing biosurfactants to mitigate disease spread.
UMMDA - Universal Multipurpose Matter Detection Application using AI
“UMMDA” USPTO and WIPO Patents pending worldwide. The UMMDA is an Artificial Intelligence and Machine Learning Apparatus that detects all types of Bacteria, Viruses, Fungus, Allergens and Micro Organisms (all types of Medical matter) abnormal cells, bodily fluids, and abnormal blood cells with accuracy that can be dialed up or down in real time. See Database example webpage de3.ai/database to see a general understanding of how ABIS database works.