• Insights
    • Blog
    • Perspectives
    • Webinars
  • Offerings
    • Strategic Innovation
    • Digital innovation
    • Product innovation
    • High-tech innovation
    • On-site consulting
  • Markets
    • Space & security
    • FMCG
    • Life sciences
    • Industry
  • Capabilities
    • AILab
    • DesignLab
    • DigitalLab
    • EmbeddedLab
    • FabLab
    • InnoLab
    • MechLab
    • OpenLab
    • OpticsLab
    • PhysicsLab
  • Technologies
    • Technology portfolio
    • IoT & sensors
    • AI & data science
    • Robotics & autonomy
    • Cooling, heating & fluidics
  • About
    • News
    • Our story
  • Careers
  • Contact
Verhaert Masters in InnovationVerhaert Masters in Innovation
Verhaert Masters in InnovationVerhaert Masters in Innovation
  • Insights
        • Blog
        • Perspectives
        • Webinars
        • FEATURED
          Report 'AI in R&D'
  • Offerings
        • Strategic
          innovation
        • Digital
          innovation
        • Product
          innovation
        • High-tech
          innovation
        • On-site
          consulting
        • FEATURED
          Innovation Academy
  • Markets
        • Space & defense
        • FMCG
        • Life sciences
        • Industry
  • Capabilities
        • AILab
        • DesignLab
        • DigitalLab
        • EmbeddedLab
        • FabLab
        • InnoLab
        • MechLab
        • OpenLab
        • OpticsLab
        • PhysicsLab
  • Technologies
        • IoT & sensors
        • AI & data science
        • Robotics & autonomy
        • Cooling, heating & fluidics
        • Optics
  • About
        • News
        • Our story
  • Careers
  • Contact

Machine learning MEMS, enabling affordable costs & power consumption

23 February 2022 Posted by Dirck Seynaeve FMCG & consumer, Perspectives, Product innovation

Machine learning MEMS (Micro-Electro-Mechanical Systems) are finding a growing number of applications in transport, smart homes, entertainment, personal assistants and IoT. In the coming years, it’s expected that the market growth of ML-enabled MEMS will go above 10%. Why you may ask? They enable costs and power consumption at costs that edge and cloud AI solutions can only dream of.

Perspective machine learning MEMS

Local data processing & analysis

The last few years we’ve seen that more and more advanced algorithms and machine learning capabilities are integrated within the MEMS. This allows for processing and interpreting data on the premise in real time. These devices are mostly equipped with multiple integrated sensors and possibly external sensors connected to the device. ML-MEMS can be programmed to analyze the sensor data for specific requirements and can make decisions by learning new data patterns.

Having these machine learning capabilities built-in offers various advantages for the product compared to dedicated edge AI ASICs or processing in the cloud. On the one hand, there’s the pricing because the device will cost less to build combined with not having to pay edge AI and data costs and processing costs in the cloud. On the other hand, they reduce or avoid the amount of data sent to local or cloud data storage, so they also have far less impact on the environment.

Reducing power consumption

One of the biggest advantages of ML-MEMS is their power saving capability, which is of huge importance for battery powered devices. Most of the sensor data processing consumes far lower power (ex. of 1/100 can be reached) of what the microprocessor would need in terms of power. Subsequently, this leads to a lower demand from CPU resources resulting in lower cost versions.

As a continuous stream of data is processed using the MEMS integrated algorithm/AI, the MEMS can take the role of watchdog, leaving the processor of the device in sleep mode only consuming a few micro-amps. Next, the MEMS are able to wake up the entire module processor and/or system based upon the MEMS own pre-programmed decision making, resulting in lower power consumption.

Download the perspective to continue reading on the benefits of using machine learning MEMS, and future application opportunities.

Tags: Artificial intelligenceInternet of Things

You also might be interested in

Featured image - Perspective - Digital transformation by business model design

Digital transformation by business model design

Mar 26, 2020

Business model design can create the rapid digital transformation necessary to innovate business models, business processes and workforce.

Featured image - Perspective - 5G: key for the future

5G: key for the future

Aug 28, 2020

5G is the next generation wireless communication technology, introduced by cellular network providers to make our lives more autonomous.

Featured image - Perspective - Artificial intelligence

Now is the time for Artificial Intelligence

Jan 22, 2019

Waiting for the right moment to start developing AI based products? Roy Amara’s Law teaches us that there is no time to waste.

NEWSLETTER
OTHER CONTENT
  • Building the digital backbone of smart, connected devices
  • Reshoring revisited: manufacturing devices in Europe
  • Personalized healthcare, from risk to impact
Verhaert group

Verhaert Masters in Innovation is a pioneering innovation group helping companies and entrepreneurs to innovate, creating new products, businesses and services.

Verhaert icon LinkedIn Verhaert icon YouTube Verhaert icon Instagram Verhaert icon phone Verhaert icon mail

Offerings
Markets
Capabilities
Technologies
Perspectives
Blogs
Webinars
About
News
Careers
Contact

© 1969-2025 • Verhaert New Products & Services NV • BE 0439.039.420 • Privacy policy • Terms of use