Chơi lô trực tuyếnAccurately locate devices in all environments worldwide
Enable location with customizable SDKs and APIs
Position devices even without a network connection
Chơi lô trực tuyếnAccurate positioning without additional hardware
Chơi lô trực tuyếnProvide context to device movements with geofences
Leverage accurate location intelligence to gain a deep understanding of consumers and competitors
Model population behaviors with confidence
Chơi lô trực tuyếnUnderstand foot traffic patterns
See when devices approach and enter venues
Uncover consumer insights and preferences
Chơi lô trực tuyếnIdentify brand-loyal frequent fliers
Advertise to specific and relevant segments
Provide context to device movements with geofences
Accurately locate devices in all environments worldwide
Enable location with customizable SDKs and APIs
Chơi lô trực tuyếnPosition devices even without a network connection
Accurate positioning without additional hardware
Provide context to device movements with geofences
Chơi lô trực tuyếnLeverage accurate location intelligence to gain a deep understanding of consumers and competitors
Chơi lô trực tuyếnModel population behaviors with confidence
Understand foot traffic patterns
See when devices approach and enter venues
Uncover consumer insights and preferences
Chơi lô trực tuyếnIdentify brand-loyal frequent fliers
Advertise to specific and relevant segments
Provide context to device movements with geofences
TIDE (Tiled Device Estimates) provides de-identified counts of location requests and unique devices within an approximately 100x100 meter (hectare) tile for every hour of a week. The data is categorized by source type (IoT, App-based, etc) and localized into every timezone.
Crowd detection, origin and destination mapping to high activity areas.
Example: How does crowd density correlate to known incidents of violent crimes?
Activity measurement for targeting fiber build-outs, cell antenna expansion and optimization of communication and data networks.
Example: What are the high activity tiles in a metropolitan area where there is dense WiFi but that are currently underserved by fiber?
Activity graphing for time of day and time of week to optimize placement of crowd sensitive or dependent commercial or public properties.
Example: Where are the busy places with bakery customers where I should open my next Panera?
TIDE5 (or finer) discretization of where APs are detected during conventional traffic patterns vs during a storm surge, floods, earthquakes or other events highly disruptive to communication networks.
Example: Where are the places that have the highest value internet infrastructure (most functioning WiFi access points and cell antennas) during landfall of a major hurricane?
Chơi lô trực tuyếnTide Pool/tiled device counts/default distribution format (csv; partition=ymdh)
Tileid(tide5) | 1234ABCEF | Collapsing hexadecimal; 1:16:256:4096... |
b/t |
---|---|---|---|
time_ymdh | 2017-08-17 14 | UTC; timestamp to hour (local/umts) | ts |
hour_of_week | 167 | Local time part; 12am-12:59am = 0 (SUN) |
int |
hour_of_day | 23 | Local time part; 12am-12:59am = 0 | int |
latitude | 42.351189 | signed; 6 digits of precision .> | in-tile float |
longitude | -71.040664 | signed; 6 digits of precision .> | in-tile float |
rlx_count | 1618 | count of returned locations logged within tile for hour | int |
devices | 64 | count of confirmed devices within tile for hour | int |
cateogry_id, source | 301 | Variable: signal source (os, app_class, stream) | int |
The above description outlines the default distribution of the TIDE product. Because time and space are essentially two knobs that Skyhook can use to produce finer or coarser mesh outputs, the hours and tiles can be delivered as more or less granular samples based on the requirements of any location-critical use case.
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