APPLICATIONS NEWS

Optical sensors attached to a smart phone to measure pollution

29 May 2014

Optical sensors attached to a smart phone to measure pollution
The smart phone fine dust sensor is intended to measure concentration in real time.Credit: Patrick Langer, KIT


Researchers from the Karlsruhe Institute of Technology (KIT) in Germany are developing optical sensors that can be connected to a smart phone with magnets to measure the levels of dust pollution in the air. Through a corresponding app, users will be able to share measurements with other users in the same city, helping to create real-time fine dust pollution maps for different locations. The invention, which is anticipated to be completed by next year, will allow the general public to directly look up the pollution levels of places such as jogging routes, local parks, or even where they plan to visit on holiday.

The principle of fine dust measurements using a smart phone corresponds to that of simple optical sensors, explained computer scientist Matthias Budde: ‘Instead of the conventional infrared LED in the sensor, the flashlight of the smart phone emits light into the measurement area. This light is scattered by the possibly existing dust or smoke. The camera serves as a receptor and takes a picture representing the measurement result. The brightness of the pixels can then be converted into the dust concentration.’ Budde developed the system as a member of the research group TECO of KIT’s Chair for Pervasive Computing.

The computer scientists have carried out comparative measurements to prove that the principle works. The smart phone sensors are not yet as precise as specialised instruments that measure pollution. However, their costs are much lower. ‘Detectors at the official measurement stations operated by the Baden-Württemberg State Agency for the Environment, Measurement, and Nature Conservation are very precise, but also very large, very expensive, and static. In Karlsruhe, for instance, only two measurement stations have been established,’ Budde pointed out.

He plans to enhance accuracy by a high measurement density. Measurements of many, closely adjacent sensors may be combined to reduce inaccurate results. Thus, measurement errors could be reduced. Due to their close vicinity, the sensors might also be calibrated against each other. Budde thinks that a potential application scenario is joint measurement or participatory sensing, whereby interested citizens measure data at various places in their city and share them. The data may then be used to draw up a fine dust pollution map for the respective city in real time.

The sensor is planned to be attached to the smart phone by means of a magnet, for instance, and adaptation of electronics will not be required. Users who want to join participatory sensing will download the corresponding app, and at the desired measurement point can attach the sensor is to the smart phone, and take a photo or a video for measurement. The images can be evaluated locally or transmitted to a computer system that combines these data with other measurements and sends them back. Then, the fine dust concentration is displayed by the phone.

Presently, the smart phone sensor can measure concentrations of about one microgram per cubic meter, which is sufficient for detecting coarse dust and smoke, but not for typical fine dust concentrations in the microgram range. The scientists now plan to further increase the sensitivity of the sensors by bundling the flashlight in the sensor using hemispherical lenses. This principle is realised in a recently produced, far smaller second prototype. In addition, the evaluation algorithms and the smart phones themselves will be further developed.

In the future, the devices will no longer compress the photos automatically, but also be able to supply raw data. This promises to increase the accuracy of the measurement results even further. Budde reckons that a smart phone sensor able to detect typical fine dust will have been developed in the course of next year.

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