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Hi,
Thanks for your interest in SCiO!
We should note that SCiO is NOT a medical device and should NOT be relied on to protect you from allergens under any circumstances. Since SCiO is designed to measure small portions of a sample or food at a time, it cannot guarantee the absence of specific molecules on your plate, or in a serving.
Ayelet,
The Consumer Physics Team
Hi all,
Thanks for reporting the issue and for suggesting the work-around.
The problem was transferred to our software team.
We will update!
Ayelet,
The Consumer Physics Team
Hi Gaurav,
Currently the login view is independent. The next Mobile SDK version will contain a different login flow.
In the meantime, you can use it the similarly to the sample app (see “viewWillAppear” in ModelsViewController.m file).
Let us know if that was helpful.
Ayelet
Hi Ben and Riel,
We would like to share that Consumer Physics underwent deep investigation in this area in the last months and found that the active ingredients in cannabis are most likely not detectable in SCiO’s current wavelength.
Please feel free to contact us with any further questions and comments.
Ayelet,
The Consumer Physics Team
Hi,
1. As part of the authentication protocol we are using, the access is available only after login through our login page. We may change that method in the future.
2. Calculating confidence level value is in our road map, the feature will be available in the future.
3. Unfortunately I didn’t get your question. Can you elaborate?
Ayelet,
The Consumer Physics Team
Hi,
SCiO typically detects materials in concentrations of 1% or higher. Concentration levels of 1% or less may also be feasible for some materials, however this is very rare.
The exact specifications depend on the SCiO application being used and material being analyzed.
The accuracy depends on the application and on the quality and size of the database. The greater the specificity and the higher number of scans in the database, the more accurate the application will be. For example, an item containing few components, such as a mixture of water and sugar, will be considered more specific and therefore its application will generally be more accurate than that of juice, which largely contains water and sugar but also various additional ingredients.
Improving SCiO’s accuracy is definitely on our roadmap, both software and hardware improvements are under development at the moment. This may affect SCiO capability to detect substances in lower concentrations more accurately.
Ayelet,
The ConsumerPhysics Team
Hi Edmir,
Just to let you know: SCiO can identify polymers textiles and fabrics, but with limitations. Colors may change the IR spectrum, making it impossible to identify the plastic (for example, many black plastics are not only black in the visible, but also in IR, so practically they have no spectral signature for SCiO to measure).
Further research is required either by us or by one of you, the developers community.
Ayelet,
The ConsumerPhysics Team
Hi Roger,
Currently, according to our terms and conditions guidelines, samples and scans collected by developers are their proprietary data.
Developers can charge for downloading their SCiO based applications from google store.
Ayelet,
The ConsumerPhysics Team
Hi all!
Plant nutrient and soil analysis are interesting fields for SCiO which we are exploring. Specifically as it relates to the above mentioned substances, further experimentation and model development is needed. This can be done either by us or by you and other members in the developers community with our SCiO Development Kit (Devkit).
Two things should be taken into consideration when working towards an application such as the one you have suggested. First, as SCiO can only detect components in concentrations which are above 1%, some micro-nutrients will not be detectable. This requires further research. In addition, it should be noted that building the database for such an application requires access to samples and their chemical characteristics.Improving SCiO’s accuracy is definitely on our roadmap, both software and hardware improvements are under development at the moment. This may affect SCiO capability to detect substances in lower concentrations more accurately.
Ayelet,
The ConsumerPhysics Team
Dear Dr. Tan,
Generally speaking, metal does not allow light in. Everything is reflected off the surface, which means SCiO won’t have any molecular fingerprint when scanning a piece of metal and the current configuration of SCiO most likely won’t support metal detection or metal toxins in matters.
As for gas scanning, SCiO is not designed for the scanning of gaseous materials. The reflectance of them is too small and they are usually very diluted. This would require a very long optical path in order to receive a decent signal.
Ayelet,
The ConsumerPhysics Team
Hi Gaurav,
The problem was transferred to our software team.
We will update.
Ayelet,
The ConsumerPhysics Team
Hi Stephen,
Thanks for the note.
We will take it into consideration in our next versions release.
Ayelet
ConsumerPhysics
Hi Zaki,
You can find instructions in our online guide, opened by pressing ‘Help’ button in the upper right corner of the screen.
Ayelet,
The ConsumerPhysics Team
Hi Jack,
We are very excited to see our developer community growing every day and we are thrilled that you are a part of it.
Just to remind you of the current mathematical algorithms as part of our pre-processing method options:
Processed (only): Assumes Beer-Lambert model is valid, and transforms the measured signal to be linear with concentration by doing a log transform and adjusting the result for noise and deviations from the model.
Normalized (only): Performs normalization of the signal. This is meant to compensate for changing measurement conditions (e.g. varied scanning distances) that typically occur from sample to sample. Y axis still means reflectance but in normalized units instead of raw reflectance.
Both Processed and Normalized: First assumes Beet-Lambert model (Processed) and then normalizes the results to compensate for differences in the optical path between samples. This is useful, for example, when there is variation in the thickness of the samples.
Both (log)R))” and Normalized: Similar to Processed and Normalized, uses a more aggressive form of Processed. Adds more noise, but in some cases may be the only way to create a good model.
Typically, different models and types of samples will require different pre-processing methods. You should both choose the pre-processing method to match your experimental setup and optimize the performance of your model. If you planned and gathered your data correctly, these efforts will coincide.
An expert mode of SCiO lab which enable users to apply different mathematical algorithms such as: Log, Derivative and SNV, will be released in the near future.
Attached is a screenshot of this new feature.
Ayelet,
The ConsumerPhysics Team
