Developer Terms and Conditions › The Development › Android development › Scio device supports only Bluetooth Low Energy android devices?
- This topic has 10 replies, 4 voices, and was last updated 8 years, 9 months ago by Scott.
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August 19, 2015 at 1:57 pm #1773Randhir KumarParticipant
I was going through tech specs given on your website for scio devices. In which you have mentioned that it will only support Bluetooth Low Energy (BLE) android devices. So will it not support Bluetooth enabled devices?
Waiting for response.
August 27, 2015 at 9:48 am #1890HagaiKeymasterCan you please give examples of Bluetooth enables devices that you are referring to?
August 28, 2015 at 5:10 am #1898Randhir KumarParticipantAugust 28, 2015 at 4:08 pm #1899rejsharpParticipantHi Randhir : There is an Android App called BLE Checker. You can see if your phone supports BT4 or not.
Please note that BLE = Bluetooth Low Energy = Bluetooth Smart = BT 4.0 and newer.
It needs the right hardware, and new phones coming with Android 4.3 and above should have it.
BUT – the BT implementation under Android 4.3 was rubbish. Android 4.4 was better, and Android 5 seems quite good.Also note that upgrading the OS version on an OLDER phone does NOT bring BTLE as the hardware is not there.
Best regards, Roger
September 18, 2015 at 10:46 am #2110Randhir KumarParticipantThanks rejsharp.
I also have one doubt that there is no proper documentation for developer on sciolab.consumerphysics.com which can explain to create models for any food material. Documentation on above link just provide some details but not that how to study this graph and how to bind attribute to actual values.
Can you please help or provide some document for the same?
Thanks in advance.
September 25, 2015 at 1:16 pm #2152rejsharpParticipantHi Randhir:
Your last question would be better posted under Molecular Sensing Models, rather than Android Dev.
Please can you be more specific, orgive an example of what you want to achieve?- This reply was modified 9 years ago by rejsharp.
September 29, 2015 at 12:56 pm #2158Randhir KumarParticipantHi RejSharp,
I have many doubts for Scio but to be specific I will try to ask my doubts one by one.
My 1st doubt: Suppose I want to scan one food material (say milk), So I want to add attributes like Fat, Protein, Lactose or Calcium. Suppose I have added also. But How will these attributes will bind to my scanned sample. Means How scio will come to know that my attribute calcium is coming in the spectrum because it is defined by me not by scio guys.
I hope it makes clear., if not please let me know.
Randhir.
October 1, 2015 at 8:14 am #2173rejsharpParticipant@ Randhir:
It works like this:-
Step 1: Create the collection “Milk” with attributes you are interested in. Remember one for unique sample ID.
Step 2: Scan your samples, adding as much info as you can (maybe just Cow Milk, Goat Milk, and unique ID.
Step 3: Make lab analysis of the attributes per unique sample ID
Step 4: Go back into your sample set and add back the lab values against each sample.
Step 5: Create the models for each attribute, and check that they look OK. Take more samples, and clean bad data as appropriate.
Step 6: Test on fresh samples and compare with lab analysis to confirm that it works.It is NOT enough to take the nutritional values from the labels, manufacturing variance is too great.
You could use label data as a very rough first try, but be sure to junk that data later.October 1, 2015 at 11:52 am #2174Randhir KumarParticipantThanks a lot for your information.
Next doubt: Suppose we have well defined model. Now I scan an unknown sample then how scio lab/sdk will provide me information or results back to mobile. means what they will provide graph differentiation, attributes values difference or end parameters like RMSE, R2.
To conclude this, I want to know what type of output result will be coming when we scan unknown sample wrt existing sample with working model.
Randhir.
January 3, 2016 at 12:11 am #2510ScottParticipantHi,
It would help us other readers to start a new topic for each question; the original topic of this thread is Bluetooth Low Energy.
Concerning Rejsharp’s last paragraph, other reasons to not rely on labels is that some may be wrong unintentionally (such as spoiled milk or undocumented supplier changes), while others may be fraudulent. Also, there may be lab variations — if there are multiple ways to analyze something, you will want the one which is accurate to well under 1%. For food, you have the additional complication of bioavailability.
–Scott.
January 3, 2016 at 5:45 am #2518ScottParticipantAlso for food, the type of food preparation will generally have a major effect on toxins and on nutrient bioavailability.
–Scott.
P.S. Off-Topic: I keep getting distracted by happy-dance face.
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