Back in the early 80s, the only way to test your sugar levels was a ketone urine test. I’m no doctor but typically it takes about 24 hours for your body to enter ketoacidosis and 2 to 4 days to see ketones in your urine. That means by the time you get a ‘positive’ test, the ‘time to act’ has passed. It’s already too late to stop it from happening; four days in, all you can do is try to improve the current situation and return to some sort of normal. I don’t even know if you could really trust the ‘data’ because the reality is, you’ve already damaged your organs by waiting that long. And over years, because you only tested when you felt bad, say once or twice a month, it’s an extremely dangerous way to live.
A decade later, technology had advanced far enough that sugar level could be tested by blood. It was revolutionary because you could know your sugars on the spot, and know when to take insulin or when to get food. For more than 30 years, I would prick my fingers up to 10 times a day before and after I ate, and any other time I need some clarity. It worked, for the most part. But different testers were more accurate than others. You couldn’t always trust data, which was especially inaccurate at high numbers. And sometimes there was a noticeable mismatch between how I felt versus what the tester was telling me. But it was certainly better than a urine test.
Just recently, now in my 41st year of being a diabetic, I finally got a DexCom Continuous Glucose Monitoring (CGM) system. What a life changer! It automatically takes a reading every 5 minutes, that’s 288 sugar level readings a day. At any time, I can see my current level plus if I’m trending up or down. It alerts for sugars that are too high or too low, even when I’m sleeping. It calculates if my sugars are rising or falling too quickly to tell me I should take action and how quickly. You can log events, like insulin and carb intake, against the data to identify patterns. For example, I found out that caffeine first thing in the morning instantly raises my blood sugar level by 200 points. Mind blowing. My body treats a diet coke (my fav!) like a carb. I never knew that. How could I? I can now look at my day in real time and learn how to better match insulin and food to keep tighter control. I can trust the numbers and have context with the trends. No more guessing. With enough data, it’ll even give me a 12-day average to mimic my A1C and can correlate patterns automatically. I cannot tell you how excited I am as a diabetic, and as an engineer, to have so much data at my fingertips. It has afforded me a way of life I’ve never imagined! I’ll never go back to tester strips.
So why do I share all of this? If it hasn’t already been made evident, this is a story about data and data integrity. My journey went from using something very inaccurate that I used bimonthly to something more accurate that I used up to 10 times a day but still lacked context, to something automated, accurate, and streamed with some AI.
This same evolution is taking place in processing plants around the world. More than a century ago, we looked at plant data historically only when necessary—safety or regulatory events—analogous to the ketones in the urine test. Then in the 1920s, we started to monitor data in control room HMIs, a spot check, to tell us when certain boundaries were breached and make improvements; a lot like the blood test. But we still had no context. Today, it’s possible to monitor hundreds of thousands of real time data streams to automatically determine when ‘undetectable to the naked eye’ anomalies occur, like my CGM, and take immediate action. But most plants are still in the tester strips stage—not taking full advantage of the technology that exists to make life so much easier!
If you want to revolutionize the way you use data, how you operate your plant, or how you empower your operators to make data-driven decisions with confidence, you need APERIO. APERIO is the CGM equivalent for your operational data. Powered by AI machine learning, APERIO automatically validates operational data at scale to improve data accuracy, security, and value, allowing for better, smarter business decisions based on real-time, trusted, superior data. (Forgive me, but I wouldn’t be a good marketer if I didn’t have a CTA at the end!)