How is time distrubuted as part of NITZ - gsm

I am trying to understand the time distribution in GSM using the NITZ (Network Identify and Time Zone). Is there any documentation around this feature? I am trying to find which component (HLR,MSC,BSS etc) is involved in the time distribution before the Android phone can use the time from the network.

Related

Can you develop an app for the Microsoft band, without a corresponding mobile app always being connected?

I have several Microsoft bands, to be used as part of a group health initiative. I intend to develop a single app on a tablet which will pull the data from the bands. This will be a manual process, there will not be a constant connection to the tablet and no connection to Microsoft Health.
Does anyone know if this is possible?
Thanks
Emma
The general answer is no: Historical sensor values are not stored or buffered on the Band itself.
It does however depend on what sensors you are interested in. The sensor values are not buffered, so you can only read the current (realtime) value of the sensors.
But sensors such as pedometer and distance are incrementing over time, so these values will make sense even though you are only connected once in a while. Whereas for, e.g., the heart rate and skin temperature, you will only get the current (realtime) value.
So it depends on your use case.

Accelerometer readings of zero every other ReadingChanged invocation

I adapted slightly the Accelerometer sample from the SDK to save the readings, and it looks like every other reading gives x:0, y:0, z:0... is that to be expected?
Will there be an option to specify a sample time, so I can get readings every n milliseconds, for instance?
What platform are you using the SDK with?
As for different polling intervals, that is not exposed currently. You can add feature requests for future Microsoft Band SDK versions at: http://microsofthealth.uservoice.com/

Sub Second iBeacon Monitoring

I have no hands on experience with BLE and beacons at this point, and am having a hard time figuring out the viability of using them in a particular manner. Wondering if anyone can provide some high level feedback about the viability of this use case:
The goal is to use beacons to track a running race. Runners with their smartphones would be able to log times when they hit various beacons spread throughout an indoor course. Pretty simple scenario.
The problems that I foresee are 1) the ability to continuously scan for beacons at sub second intervals, and 2) the ability to then determine closest range to the beacon at sub second intervals.
I've tried parsing through the estimote and kontakt.io SDKs and am not certain that what I want to do is entirely possible or feasible with these particular beacons (or any for that matter). Further, would there be any device (the smartphones) specific limitations that would apply?
Thanks!
If you are using Estimote SDK you can set this property on BeaconManager.
See BeaconManager#setForegroundScanPeriod. SDK Docs

Zigbee mesh networking

I'm making an application for a running competition on a fixed track. I'm investigating what systems could be used and tough of using a stick containing a GPS/DGPS module and a Zigbee enabled chip to communicate the location to a server.
I've researched the subject (on the internet) but I was wondering if anyone has some practical advice/experience with using a Zigbee mesh/star topology in a dynamic environment wich could apply to this use case. I'm also very interested in using a mesh topology where the data is transmitted (hopping) trough the different Zigbee modules to the server.
Runners are holding a stick; run around the track and than pass the stick on to the next team member.
I am not particularly clear about your goal. But I'd like to say a few things.
First, using GPS/DGPS to measure which team reaches the finish line is inaccurate. Raw GPS data is horrible in accuracy (varying in 1 - 10 meters, well, around that), also the sampling rate of a GPS module is low (say once a second?) How do you determine exactly which team reaches the finish line first?
Second, to use a mobile ZigBee chip to communicate in real-time is hard. I assume your stick has a ZigBee end device. When it is moving (which in your case is pretty fast), it must dynamically find and associate with new parent routers, which takes time and depending on the wireless environment, it might involve several retries. So you will imagine a packet is only successfully delivered to the other end after 100ms or even a second. This might not be a problem if your stick records the exact time when a team reaches the finish line. Since you have a GPS module in the stick so there is no problem in getting very accurate time.

QGeoPositionInfoSource: What and where are the system's default "sources of location data"?

The following quote is from this link: http://apidocs.meego.com/1.2-preview/qtmobility/qgeopositioninfosource.html#createDefaultSource
Creates and returns a position source
with the given parent that reads from
the system's default sources of
location data, or the plugin with the
highest available priority.
What and where are the system's default "sources of location data"? Any examples?
And what do I need to read to understand these concepts?
The default source depends on the Device.
As to the question regarding what the sources might be , here is an extract from forum.nokia documentation regarding symbian phones , although this is mostly true in reference to other devices and platforms as well
GPS based: It can provide location estimation with accuracy from 10 to 30 meters. Depending on the actual technology and the state of GPS module, time to first fix varies from several seconds to minutes. Time to next fix is normally 1 second. It may not work indoor. The GPS module, which makes location estimation, may reside internally (e.g. integrated GPS) or externally (e.g. Bluetooth GPS) of the terminal.
Assisted GPS: Assisted GPS technology improves performance (i.e. time to first fix and sensitivity) by acquiring assistant data from an assistance server. The mobile phone receives the assistant data from wireless network. Depends on the operator and subscription, end user may have to pay for receiving assistant data.
Network based: It can provide location estimation with accuracy from a hundred meter to several kilometers. Time to first fix and time to next fix is normally within 10 seconds. It works also indoor. It normally requires support from operator.

Resources