Re:Analyzing My Google Location History
by ehsankia on Thursday November 22, 2018 @07:48PM
(#18513597)
> I assumed confidence to be the probability of each task. However, often they do not add up to 100. If they do not represent probabilities what do they represent?
The probability of each being true independently?
> How can Google possibly predict activity type between IN_TWO_WHEELER_VEHICLE vs IN_FOUR_WHEELER_VEHICLE ?!
Two wheel vehicles can often make it through traffic, in between cars.
Re:Analyzing My Google Location History
by egypturnash on Thursday November 22, 2018 @08:12PM
(#18513685)
Measuring how much the phone rolled back and forth could be a factor, too. You don’t have to keep a car balanced, you do have to keep a bike/scooter/motorcycle balanced.
Re:Analyzing My Google Location History
by nl on Friday November 23, 2018 @01:48AM
(#18514818)
I going to bet there are more bike driving people with Android phones in places like Thailand, Indonesia, India and the Philippines where on-road behavior is more similar to each other than to the US.
I think it's a pretty hard problem, and we shouldn't be surprised if the accuracy there is low.
Re:Analyzing My Google Location History
by cameldrv on Thursday November 22, 2018 @11:32PM
(#18514373)
It's probably a combination of features, but the suspensions are different, and two wheelers lean when they turn, which should be easy to distinguish from the accelerometer and gyros.
Re:Analyzing My Google Location History
by jayd16 on Thursday November 22, 2018 @09:02PM
(#18513862)
Seems feasible to detect a user at above foot speed,that appears to be stopping at intersections but seems to be more immune to congestion than others and label it as a two wheeled vehicle.
Re:Analyzing My Google Location History
by lars512 on Thursday November 22, 2018 @09:56PM
(#18514028)
I did something like this in a quantified self phase, it's fun to see the location patterns. I was gridding locations into buckets and scoring the entropy over time, to see how diverse the set of locations I was going to was. Long story short, not that diverse. Just over 1 bit was enough! (think: home or work)
Re:Analyzing My Google Location History
by jfim on Thursday November 22, 2018 @10:20PM
(#18514113)
We actually did that several years ago in our data viz lab. All of the (willing) lab members tracked their location data and one student developed a way to track and visualize co-occurrences of people over time [1].
Another ways to visualize this kind of information is to use space time cube maps, which turn the time axis into the z-axis for trajectory visualization; GeoTime[2] is the most well known implementation of it AFAIK.
Re:Analyzing My Google Location History
by elboru on Friday November 23, 2018 @01:03AM
(#18514669)
Uhmm, maybe it depends on the phone? I backpacked Europe 4 years ago without a data plan and I have all my location history logged, it seems like it kept it on my phone while offline and then it uploaded it when connected, I used a Galaxy S5 btw.
Re:Analyzing My Google Location History
by pmontra on Friday November 23, 2018 @07:29AM
(#18516013)
I'd prefer it to be saved locally or sent to a server of mine with some standard protocol (maybe NMEA 0183 over HTTP POSTs) and never to Google. Of course I could write an app for that (and I did some 8 years ago) but it would be much easier if the OS would cooperate.
By the way, I disabled location services on my devices to prevent at least this form of spying on me.
Re:Analyzing My Google Location History
by code_duck on Thursday November 22, 2018 @11:15PM
(#18514314)
Or you’re getting an IP from somewhere associated with a different region. This happens all the time with my cell connection - it seems the company uses spare Verizon capacity, and when I (or someone else) looks up my 4G is, it’s all over the US with no connection to my actual location.
The probability of each being true independently?
> How can Google possibly predict activity type between IN_TWO_WHEELER_VEHICLE vs IN_FOUR_WHEELER_VEHICLE ?!
Two wheel vehicles can often make it through traffic, in between cars.
Could they be using this from accelerometer data instead of GPS? https://github.com/guillaume-chevalier/LSTM-Human-Activity-R...
I think it's a pretty hard problem, and we shouldn't be surprised if the accuracy there is low.
https://dirkjan.ochtman.nl/writing/2012/11/28/tracing-a-path...
"The device angle relative to gravity changed significantly."
-- https://developers.google.com/android/reference/com/google/a...
Another ways to visualize this kind of information is to use space time cube maps, which turn the time axis into the z-axis for trajectory visualization; GeoTime[2] is the most well known implementation of it AFAIK.
[1] http://profs.etsmtl.ca/mmcguffin/research/2016-gupta-Movemen... [2] https://geotime.com/products/geotime/
By the way, I disabled location services on my devices to prevent at least this form of spying on me.
It uses MQTT, which is probably fault tolerant/store data locally if it can't connect to the server right now.
Sounds more like your gmail account was compromised