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Common Pitfalls of IoT Projects: Reason Two

Avoid Quantity Rather Than Quality

Imagine solving all of the challenges of getting a device to talk and uplifting the data to the Cloud – only to find out it’s bad data. We actually see this happen a lot. Incorrect big data that results in false alerts being created or incorrect product levels being reported are especially bad.Imagine that you make an IoT-capable soap dispenser and that you can detect when the soap inside the dispenser is running low. Knowing this, you could send a message to the custodian on duty to go refill it, right? Well, if your IoT system is generating incorrect data, you might be sending your custodian alerts when the dispenser is only half empty. Maybe the custodian will allow the system a few false alerts, but if it happens regularly, they will just simply start to ignore the messages because they know they are not accurate. And, if you’re the procurement manager trying to figure out how much soap to order, inaccurate product level information is going to really hamper your efforts to place your reorders correctly.
For IoT projects, inaccurate data kills any trust users have in an automated system and is a major reason IoT projects fail. Bottom line – a successful IoT project starts with good data and good data has to be a priority for your team.

Read more about the common pitfalls and how to overcome them in our next blog posts.

Topics: IoT, Obstacles, Big Data

With 13 years of experience designing and developing applications, TeraCode strives to help readers navigate the winding IoT journey through the tech buzzwords and decisions you'll encounter.

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