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The top 4 benefits of IoT data management

From vehicles and buildings to toothbrushes and toasters, everything around us is increasingly controlled by sensors. This brings IoT data management on the scene. While no one really needs an email notification when their toast is ready, it’s clear people are more comfortable automating their lives. This creates greater opportunities to develop smart products that collect useful data and reduce the time spent on manual tasks.

But it also means businesses face a constant challenge. Whether you’re manufacturing a fleet of connected trucks or operating a smart building, the IoT is built for people. Unfortunately, people apply technology in ways that are difficult to predict. Equipping businesses with the right tools to understand actual usage is essential to produce useful devices. That’s where collecting, storing and managing IoT data from the field comes in. Field data, which are coming back from customer usage, have a significant impact on the next iteration of a product.

Using IoT data management to create better products

IoT data management enables businesses to discover usage patterns. It also challenges assumptions made during design and development phases, identifying weaknesses in connected devices. In other words – it helps create the best connected products possible.

Before you release a product, IoT data management allows you to conduct a field test. Just as Tony Stark needed to be thrown into a few walls before his Iron Man suit was ready for battle, any product you create needs to go through a testing phase. You gather data on how it’s used to determine most likely wear-and-tear areas, expected product lifetime, environmental conditions and user behavior.

IoT data management: Data-driven product development Source: Bosch.IO
Data-driven product development

Armed with this data, you can improve design. And create a higher-quality product that offers the best user experience. For example, an automated vehicle manufacturer can identify how various parts and components are used, and assess what conditions they can withstand. When you consider that vehicle recall costs can run into millions in compensation claims (not to mention the cost to your reputation), this is a no-brainer. Collecting field data is also an important step post-launch. You can provide continuous product improvements with software updates and get important insights for your next version. Throughout the product lifetime, these insights will support the development process of new products and additional iterations. Also, they will help identify anomalies.

4 major benefits of IoT data management for your IoT strategy

1. Understand users’ needs

Automation exists to make people’s lives easier. Their needs and habits should underpin your connected devices. Exploring IoT data from the field will give you a better idea of how the product functions in a user’s day-to-day life. Maybe you have designed a smart air conditioner or lighting system that includes automation settings based on the weather. If people are overriding these settings to make a manual change, it is a sign that the product doesn’t align with their needs or expectations. IoT data management lets you optimize these smart algorithms by looking at sensory data and the points in time when a user made a change. Then you can redesign or retrain your product to offer a better user experience.

2. Predict asset wear

This also applies to connected infrastructure and assets. Foot traffic will impact a smart bridge or floodgate. IoT data is essential to understand expected wear-and-tear and plan for maintenance and repairs. By conducting this exploration throughout its life cycle, you can also identify if users are operating outside of anticipated patterns. Combined, these insights let you pinpoint areas where the product needs reinforcements or additional features.

3. Enable resource efficiency

The goal of automation is always efficiency but it’s easier said than done if you are working on instinct or assumptions. Data on how customers use your products allows you to make more educated decisions. For example, in a connected building, monitor how people are operating heating and lighting, assess how spaces are used and keep track of any deterioration. This lets you reduce inefficient use of time, space or energy – ultimately saving you money.

4. Create effective systems

Complex IoT solutions consist of many individual devices. Although each of them separately might work to perfection, when working as a system, they can behave in unexpected ways. It’s not enough to simply collect telemetric data from individual devices. The transmission, storing and managing of IoT data enables you to identify problems early on and validate the performance of the overall system.

Infographics showing a systematic field data explorator for IoT data management Source: Bosch.IO
Step by step: From data transfer to data analysis

Kick-starting IoT data management

Christoph Grotz

Christoph Grotz has been a Solution Architect at Bosch.IO (formerly Bosch Software Innovations) since 2012. Christoph is passionate about the Internet of Things and has gained experience through many projects inside and outside of Bosch in topics like Smart City, wireless sensor networks and connected products. In the nine years he was active in the software industry he has worked in both frontend and backend, but prefers backend. At Bosch.IO he is currently doing consulting on IoT solutions implementation.

To make sense of all data points, customers usually need a complex solution that requires lengthy ad-hoc development. This chews up budget and steals time. Based on the experience of more than a dozen IoT data management projects, these two main features were decisive for our customers:

  • A ready-made, standardized solution delivered as a service. It’s simple to use and doesn’t require extra effort to set up. For example, we deploy our IoT data management solution in the Bosch IoT Cloud or on our customers’ sites.
  • Our solution for the vehicle market supports the decoding of customer-specific formats and various automotive data specification standards. This includes ODX, Fibex, A2L, dbc, and mdf. The raw data is permanently stored in an archive, so our customers can restore the original data if needed. On the other hand, the decoded, normalized and enriched data is securely accessible by data scientists.

From a shot in the dark to informed decisions with IoT data management

When you’re dealing with large amounts of geographically dispersed IoT device data, you need a solution that not only collects but decodes and fills in the blanks, stores, and makes sense of it for you. Without access to structured data from the field, you are experimenting and developing in the dark. But with the right insights up your sleeve you can improve product development, increase efficiency and quality and simplify operations.

More information on IoT data management

How to prepare vehicle data for smart use: IoT field data management in the automotive industry.

The IoT generates tremendous quantities of data. Bosch.IO helps customers harnessing their IoT data’s potential through online analysis of device data and end-to-end processing of large data sets.

Arun Shekhawat on “Of gold and shovels in the IoT” assessing IoT data management in context with IoT business model innovation and digital transformation.