Medical Surveillance: Numerous Applications for Government Entities and Entrepreneurs
March 16, 2020
With the Corona virus capturing headlines and disrupting routines, how can smart software monitoring data help with the current problem?
DarkCyber assumes that government health professionals would want to make use of technology that reduced a Corona disruption. Enforcement professionals would understand that monitoring, alerting, and identifying functions could assist in spotting issues; for example, in a particular region.
What’s interesting is that the application of intelware systems and methods to health issues is likely to become a robust business. However, despite the effective application of established techniques, identifying signals in a stream of data is an extension of innovations reaching back to i2 Analyst Notebook and other sensemaking systems in wide use in many countries’ enforcement and intelligence agencies.
What’s different is the keen attention these monitoring, alerting, and identifying systems are attracting.
Let’s take one example: Bluedot, a company operating from Canada. Founded by an infectious disease physician, Dr. Kamran Kahn. This company was one of the first firms to highlight the threat posed by the Coronavirus. According to Diginomica, BlueDot “alerted its private sector and government clients about a cluster of unusual pneumonia cases happening around a market in Wuhan, China.”
BlueDot, founded in 2013, combined expertise in infectious disease, artificial intelligence, analytics, and flows of open source and specialized information. “How Canadian AI start-up BlueDot Spotted Coronavirus before Anyone Else Had a Clue” explains what the company did to sound the alarm:
The BlueDot engine gathers data on over 150 diseases and syndromes around the world searching every 15 minutes, 24 hours a day. This includes official data from organizations like the Center for Disease Control or the World Health Organization. But, the system also counts on less structured information. Much of BlueDot’s predictive ability comes from data it collects outside official health care sources including, for example, the worldwide movements of more than four billion travelers on commercial flights every year; human, animal and insect population data; climate data from satellites; and local information from journalists and healthcare workers, pouring through 100,000 online articles each day spanning 65 languages. BlueDot’s specialists manually classified the data, developed a taxonomy so relevant keywords could be scanned efficiently, and then applied machine learning and natural language processing to train the system. As a result, it says, only a handful of cases are flagged for human experts to analyze. BlueDot sends out regular alerts to health care, government, business, and public health clients. The alerts provide brief synopses of anomalous disease outbreaks that its AI engine has discovered and the risks they may pose.
DarkCyber interprets BlueDot’s pinpointing of the Corona virus as an important achievement. More importantly, DarkCyber sees BlueDot’s system as an example of innovators replicating the systems, methods, procedures, and outputs from intelware and policeware systems.
Independent thinkers arrive at a practical workflow to convert raw data into high-value insights. BlueDot is a company that points the way to the future of deriving actionable information from a range of content.
Some vendors of specialized software work hard to keep their systems and methods confidential and in some cases secret. Now a person interested in how some specialized software and service providers assist government agencies, intelligence professionals, and security experts can read about BlueDot in open source articles like the one cited in this blog post or work through the information on the BlueDot Web site. The company wants to hire a surveillance analyst. Click here for information.
Net net: BlueDot provides a template for innovators wanting to apply systems and methods that once were classified or confidential to commercial problems. Business intelligence may become more like traditional intelligence more quickly than some anticipated.
Stephen E Arnold, March 16, 2020
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