Big Fred is program that takes the history of the reported data and changes the SAN’s specific tolerance ranges based on the those reports. Big Fred is specifically designed to record, analyze, and detect patterns that emerge in data sets both from existing data sources and real-world reporting. One of the most difficult indicators to detect is the atypical indicators. Often truly indicative information is well divorce in apparent meaning and/or relationship to a target query. Big Fred is capable of identifying correlations between seemingly unrelated information, to determine new emerging trends or undetected relationships between data at the earliest possible time. Furthermore, Big Fred responds to user interaction. In essence, Big Fred learns as it receives feedback from user after the SAN supplies reports. The resultant machine is a dynamic, evolving, active analysis, pattern recognition, digital apparatus capable of producing hard probability models as well as providing suggestions to the user as to how best to reduce their uncertainty of their environment. For instance, to user, in the field, investigating a potential methamphetamine lab may enter a report of 50 empty lye (sodium hydroxide) bottles. Big Fred would then calculate the probability in percentages that the user has detected an indicator related to a methamphetamine lab based on the significance of the indicator and historically similar reporting. Big Fred is also capable of calculating indicator interactive and can then suggest other indicators the user may look for to reduce uncertainty (increase the percentage probability that the user has found methamphetamine relate indicators).