Intervall – BME688 Use Cases

BME688: A four-in-one
Environmental Sensor.

The BME688 is a 4-in-1 environmental sensor that combines an AI-enabled gas sensor with integrated high-linearity and high-accuracy pressure, humidity and temperature sensors.

Pressure

Humidty

Temperature

Gas

A Digital Nose.

The BME688 is like a digital nose.
It can detect gases by measuring their unique electric fingerprint and therefore distinguish different gas compositions. The BME688 can even determine the concentration of a gas or its underlying source solely based on the emitted gas composition.

NOSE	SENSOR	DIGITAL NOSE
attached to the body	location-independent	extended nose
needs some recovery time (e.g.during sleep)	always ready	hardworking nose
blind for slow and steady changes	repeatable precision	absolute nose
sensitive to special gases	sensitive for additional gases	complementary nose
individual sensitivities	calibrated and tested sensitivities	objective nose
highly emotional	sober and rational	not my own nose

A Gas Sensor That Fits Your Use Case.
Thanks to Artificial Intelligence.

Conventional gas sensors are designed to detect a single gas and are therefore highly specialised. The BME688 can be taught to understand almost any gas composition using Machine Learning.

This not only allows the BME688 to detect commonly known gases, but also more abstract gas compositions like odours and aromas. Through the new regression feature the BME688 is even able to predict the concentration of a gas or its underlying source.

Thanks to Artificial Intelligence the BME688 becomes a highly versatile gas sensor that bears the potential for countless use cases across various domains.

Machine Learning Algorithm

Machine Learning Algorithm & Use Case

Use Case

We Help You Customise the BME688 for Your Use Case.
— from Exploration to Final Algorithm.

Exploration of Gas Sensing Use Cases

Support for Hardware Configuration

Support for Data Recording

Complete Algorithm Development

Intervall combines a deep technical understanding of the BME688 with a user-centric design approach to identify actual user needs in a given context. These two perspectives allow us to effectively identify and evaluate use cases for the BME688 in your specific domain.

Intervall has conceptualised and realized multiple hardware setups and prototypes utilising the BME688. Each use case requires a specific hardware setup and sensor configuration in order to record meaningful gas data than can be used for training the BME688.

Intervall has overseen the recording of hundreds of hours of gas data with the BME688. Compiling a meaningful gas data basis is fundamental for developing a solid algorithm for the BME688.

Intervall has conceptualised and developed multiple algorithms for use cases of the BME688. The core of realising a use case for the BME688 is the development of a solid Machine Learning algorithm able to make reliable predictions in the field.

Identifying opportunity areas in a specific domain

Explore and define goals and value proposition

Rapid visualising and prototyping of ideas for evaluation

Building hardware prototypes and setups

Sensor configuration for data recording

Initial test measurements

Continuous monitoring of data recording progress and data quality

Data cleaning and curation

Develop Machine Learning concepts (architectures, verification strategies)

Set up machine learning tech stack and pipeline

ML exploration and optimisation

Deployment of final algorithm

Benefit from Our Expertise.

Co-Creator of the BME688 Ecosystem

The BME688 sensor is accompanied by the BME AI-Studio Ecosystem (AI-Studio Desktop, AI-Studio Mobile and AI-Studio Server). Intervall and Bosch Sensortec have developed the software supporting the BME688 in close collaboration. Currently Intervall is trusted with the development of new features for the BME AI-Studio Ecosystem – continuously enhancing the functionality of the BME688.

Half a Decade of Experience

Intervall has more than five years of experience in working with the BME688. Ranging from conceptualising and developing the BME AI-Studio Ecosystem, over specialised consulting on Machine Learning for gas sensing, to the development of algorithms for concrete use cases. Over the years we have gained a deep understanding of the BME688 and its characteristic behaviour.

Combination Computation and Design

Intervall combines methods of design and computational thinking. We have a deep technical understanding of the BME688, data science and machine learning which we pair with a user centric approach for understanding user needs and designing appropriate solutions. In summary we ask what is possible from a technological perspective and needed from a user perspective.

“Intervall is a reliable partner for us at Bosch Sensortec and we can highly recommend them for fast and scaleable custom use case development.”

- Dr. Richard Fix
Portfolio Manager Bosch Sensortec

Successful Applications in the Field.

BME688 for
Mobile Alarm Systems

BME688 is used in a mobile alarm system that combines multiple sensors to detect various threats like intruders, fire, hazardous gases and bad air quality.

#DataScience
#MachineLearning
#AlgorithmDevelopment
#UX/UI

a network of BME688 sensor above a forest

BME688 for
Ultra Early Wildfire Detection

BME688 is used in a network of solar-powered sensor units deployed in forests for ultra early wild fire detection. This is enabled by the BME688 detecting various gases such as carbon monoxide and hydrogen which indicate smouldering fires.

#AIStudioServer
#API
#Automization
#ContinousTraining

photo of a textile machine with a BME688 sensor

BME688 for
Textile Industry Applications

BME688 is used in a textile scanner that uses a combination of sensors to analyse textiles in an industrial context. The goal is to optimize production based on findings generated by the sensors.

#Research
#DataAnalysis
#MachineLearning
#AlgorithmDevelopment
#HardwarePrototyping

BME688: A four-in-one
Environmental Sensor.

A Digital Nose.