{"info":{"_postman_id":"d8e042de-3754-42b6-beb6-a174697eddf8","name":"Telus Insights Location API","description":"
Telus Insights solution helps customers utilize TELUS Geo-intelligence data assets and help answer a range of questions around location and movement patterns within Canada.
\nKey Highlights of TELUS Insights Location API:
\nTELUS Insights has developed a proprietary algorithm to determine the primary and secondary neighbourhood of the devices. This algorithm looks at a series of factors, such as time spent in an area, number of days spent, frequency of visits, consecutive hours, and others, to decide the primary and secondary neighbourhoods of a device. This algorithm is designed to ensure the model works in a broad range of conditions, including rural, and urban areas.
\nThe algorithm has been built in a way that the secondary neighbourhood is not confused with primary neighbourhood.
\nTo be fully representative of the Canadian population, TELUS Insights extrapolates the subscriber data based on our market share information. TELUS builds highly detailed market shares, broken down by census sub-divisions. These market shares account for many variables, including the likelihood of an individual owning multiple devices, the drop off points of access to cellular service, as well as area populations. Each device is given a multiplier to help it be representative of its home neighbourhood at a census sub-division level.
\nInsights Developer Portal enables the users to explore, interact and query the API through an intuitive interface.
\nDevoloper Portal provides self-serve capabilities on top of the API such as:
\n
In order to build automated solutions for API consumption, we recommend the following process and best practices
Request OAuth credentials by creating a ticket in the Portal. Check your My Account page in the portal to determine if you already have them.
\nTo create scripts for your favorite language you can get some code snippets from the “Example Request” section for each API on this site.
\n# Set your credentials - Check My Account Page\ncustomerId=\"\"\noauth_client_id=\"\"\noauth_client_secret=\"\"\n# OAuth config - Check My Account Page\noauth_token_endpoint=\"\"\noauth_grant_type=\"\"\noauth_scope=\"\"\nlocation_api_url=\"\"\n# Set thresholds\nwaitSecondsBeforeFetchingJobResults=300s\n# Set your request body variables. You can use the JSON preview feature in the Portal to get this info.\ninputRequestId=\"your-input-request-id\"\ninputStudyZones='\"studyzone-1\",\"studyzone-2\"'\noutputRequestId=\"your-input-output-id\"\noutputStudyZones='\"studyzone-1\",\"studyzone-2\"'\nstartTime=\"2020-10-04T00:00:00\"\nendTime=\"2020-10-06T00:00:00\"\n# See Swagger file for info on api request body\napi_path=\"home\"\napi_request_body='{\"input_geoid\": {\"requestId\": \"'${inputRequestId}'\",\"study_zone\": ['${inputStudyZones}']},\"output_geoid\": {\"requestId\": \"'${outputRequestId}'\",\"study_zone\": ['${outputStudyZones}']},\"start_time\": \"'$startTime'\",\"end_time\": \"'$endTime'\",\"time_bucket_size\": 15,\"exclusion_types\": []}'\n# Get access_token \naccess_token_expiry_time=`date`\ncurrent_date_time=`date`\necho \"Getting access token - current_date_time=$current_date_time\"\naccess_token_data=$(curl --request POST \\\n --url \"${oauth_token_endpoint}\" \\\n --header \"content-type: application/x-www-form-urlencoded\" \\\n --data grant_type=${oauth_grant_type} \\\n --data client_id=\"${oauth_client_id}\" \\\n --data client_secret=\"${oauth_client_secret}\" \\\n --data scope=\"${oauth_scope}\")\naccess_token=$(echo $access_token_data | jq --raw-output .access_token)\naccess_token_expiry_in_seconds=$(echo $access_token_data | jq --raw-output .expires_in)\naccess_token_expiry_time=$(date --date=\"+$(expr $access_token_expiry_in_seconds - 5) seconds\")\necho \"Authorization: Bearer ${access_token}\"\n# POST a Job\njobStartTime=`date \"+%Y-%m-%d %H:%M:%S\"`\njobData=$(curl --request POST \\\n --url \"${location_api_url}/count/${api_path}\" \\\n --header \"content-type: application/json\" \\\n --header \"Authorization: Bearer ${access_token}\" \\\n --header \"customerid: ${customerId}\" \\\n --data \"${api_request_body}\")\n# Retrive the Job Id\necho \"jobData=${jobData}\"\njobId=$(echo $jobData | jq --raw-output .jobId)\necho \"jobId=$jobId\"\n# Check Job Results in a loop\necho \"Starting the GET loop for a job.........\"\nstatus=\"not-done\"\nwhile [ $status != \"COMPLETE\" ]\ndo\n echo \"sleeping for $waitSecondsBeforeFetchingJobResults .... \"\n sleep $waitSecondsBeforeFetchingJobResults\n echo \"checking job status .... \"\n # Refresh access_token if its expiry time is in the past\n current_date_time=`date`\n if [[ $(date +%s -d\"$access_token_expiry_time\") -le $(date +%s -d\"$current_date_time\") ]]\n then \n echo \"Getting access token - access_token_expiry_time=$access_token_expiry_time, current_date_time=$current_date_time\"\n access_token_data=$(curl --request POST \\\n --url \"${oauth_token_endpoint}\" \\\n --header \"content-type: application/x-www-form-urlencoded\" \\\n --data grant_type=${oauth_grant_type} \\\n --data client_id=\"${oauth_client_id}\" \\\n --data client_secret=\"${oauth_client_secret}\" \\\n --data scope=\"${oauth_scope}\")\n access_token=$(echo $access_token_data | jq --raw-output .access_token)\n access_token_expiry_in_seconds=$(echo $access_token_data | jq --raw-output .expires_in)\n access_token_expiry_time=$(date --date=\"+$(expr $access_token_expiry_in_seconds - 5) seconds\")\n # echo \"Authorization: Bearer ${access_token}\"\n fi\n results=$(curl --request GET \\\n --url \"${location_api_url}/count/${api_path}/${jobId}\" \\\n --header \"Authorization: Bearer ${access_token}\" \\\n --header \"customerid: ${customerId}\")\n # Check job status\n # echo \"results=${results}\"\n status=$(echo $results | jq --raw-output .status)\n if [[ $status != \"COMPLETE\" ]]\n then \n echo \"Not complete yet, will poll again ...\"\n else\n jobEndTime=`date \"+%Y-%m-%d %H:%M:%S\"`\n echo \"Results received ...............\"\n echo \"status=$status. Job results saved to ${jobId}.json\"\n echo \"Total time taken=$(expr $(date -d \"$jobEndTime\" \"+%s\") - $(date -d \"$jobStartTime\" \"+%s\")) seconds\"\n echo \"$results\" >> ${api_path}.${jobId}.json\n fi\ndone\n\n\nCurrently Rate-limiting is not implemented for the API. However, in order to ensure the API performance and stability, it is strongly recommended that all users follow the below limitations:
\nMinimum Time Bucket Size of 15 min is allowed for queries ranging up to 1 day period
\nMinimum Time Bucket Size of 60 min is allowed only for queries ranging up to 30 days period
\nMinimum Time Bucket Size of 24 Hrs is allowed for queries more than 30 days
\nOnly run 5 concurrent queries at a time. This includes queries submitted via the API and the portal.
\nOnly run 10 queries per hour and 100 queries per day
\nWe have now made available the usage statistics at an organization level to help you understand the overall API consumption. This feature primarily provides the following:
\nThis will enable you to understand and administer your organization's usage against the plan's limit.
\n'Usage Statistics' option has been made available under 'Account Settings' as depicted below:
\nBy default, the statistics will be displayed for the current month and year which could be changed using the dropdowns.
\nThere are three parts to Usage Statistics.
\nPart 1: Primary information i.e. number of monthly API Calls and number of Study Zones queried for the selected month and year as depicted below:
\nPart 2: End-point wise breakdown of the total API Calls based on the selected month and year as depicted below:
\nPart 3: Comparison of total no. of API Calls and Study Zones queried in the current year (based on selection) and the previous year as depicted below:
\nThe processing time is proportional to the complexity of the query and the volume of the data being fetched. In order to reduce the processing time, it is highly recommended to break down your queries for smaller date ranges.
\nWhen getting an OAuth Token from the Token URL, it is preferable that you reuse the token for specified amount of expiry seconds (present inside the token JSON and set to 299 seconds). That prevents the identity system from being overwhelmed.
\nThe API is asynchronous, when a POST is submitted to start a job, a Job Id is returned. The job results can be fetched by doing a GET using the Job Id. It is recommended to wait a minimum of 5 minutes before submitting a GET for the results. Because the job results are not guaranteed within 5 minutes, we recommend that you create a loop to check the results based on the “status” field equal to “COMPLETE” that you get back in the API response.
\nTo protect our platform from overload, we recommend users not to exceed 10 queries on average per hour and 100 queries per day. Please note that these are averages for full POST and GET cycle of the request. This means that it is OK for you to submit (POST) 10 queries within a minute and then wait for them to complete (GET) within an hour.
\nWe are invested in your success and wrote this guide to help you get started in the quickest and most optimal manner. This quick Start Guide will help you analyze your first study zone and unlock your first insights. Specifically, it will cover:
\nAuthentication to Telus Insights Portal (https://insights.telus.com) will be done through Telus Client Identity. Two emails will be sent as a part of the onboarding process – first will be an informative email (from dlTelusInsights@telus.com) containing links to the Telus Insights Portal and our API Documentation and the other will be an activation/registration email through our Telus Client Identity system (do.not.reply@telus.com) that would allow you to create a password. The user ID is the email address.
\nNote: If you are already registered with Telus Client Identity, you could start accessing Telus Insights Portal once you receive the informative email from dlTelusInsights@telus.com.
\nTo authenticate to the API - https://location-api.insights.telus.com, please refer to OAuth credentials (Client Id and Secret) and the configuration details on your 'My Account' page in Telus Insights Portal. More details could be found on the API Integrations page.
\nA study zone is a location, or set of locations defined as a geospatial boundary otherwise known as a “Geo Fence” that defines an area such as a Mall, an FSA, FSA-LDU or Census boundary.
\nBefore making a POST/GET request to the Count endpoint, areas of study needs to be defined. The areas of study are a list of “Study Zones” (aka polygons) defined within the shapefile. Each Study Zone will have a series of latitude and longitudes associated with the Study Zone.
\nEach study area will be defined, uploaded and maintained in the system as a set of Latitude Longitude that encapsulate a geo fence.
\nBefore a user can query the Count endpoint, a study zone must be defined which includes a location, or group of locations you would like to include in analysis.
\nYou could either create your own Custom Shapefile using our shapefile endpoint or use one of the Public Shapefiles downloaded from Stats Canada website made available to you for your analysis.
\nPublic shapefiles are geo-spatial files that store standard areas defined by public Canadian authorities such as Census Subdivision (CSD) and Forward Sortation Areas (FSA).
\nSource of the files: Stats Canada website
\nType of files: Digital Boundary Files
\nNaming convention for shapefiles and study zones:
Original shapefiles have been broken down into Provincial files. For uniformity, shapefile and study zone name length will follow the same length requirements for custom shapefiles/study zones i.e. shapefile name will be <= 75 characters and study zone name length will be <= 50 characters.
Following is the file and shapefile naming conventions:
CSD files:
\npublic_canada_csd_CensusYear_PRCode_PRUID.zip\n\nCensus Year is the year for which file is available, PR Code is the province/territory code and PRUID is the unique identifier for each province/territory.
\nExample shapefile name: public_canada_csd_2021_bc_59.zip\nExample RequestID: public-canada-csd-2021-bc-59-zip-{random GUID}\n\nFor study zones, naming convention is 'CSD Name' followed by 'CSD Type'. There are about 50 CSDs which have duplicate CSD Name and Type combination; to uniquely identify these CSDs in the system, 'DGUID' has been appended into the study zone name.
\nExample without DGUID: Victoria(CY)\nExample with DGUID: Okanagan (Part) 1(IRI)(5937801)\n\nReferences: Dictionary, Census of Population, 2021
\nFSA files:
\npublic_canada_fsa_CensusYear_PRCode_PRUID.zip\n\nCensus Year is the year for which file is available, PR Code is the province/territory code and PRUID is the unique identifier for each province/territory.
\nExample shapefile name: public_canada_fsa_2021_bc_59.zip\nExample RequestID: public-canada-fsa-2021-bc-59-zip-{random GUID}\n\nFor study zones, CFSAUID which uniquely identifies a forward sortation area composed of three alphanumeric characters.
\nExample: V3T\n\nReferences: Forward Sortation Area, Boundary File, Reference Guide
\nRelease dates:
\nCSD Files: 2021
\nFSA Files: 2021
\nHow to use Public Shapefiles:
Public Shapefiles are made available on the Job Tool screen below the Custom Shapefiles under Shapefile/RequestID drop-down list as depicted below.
Geofence endpoint will also return the list of Public Shapfile Request IDs below the Custom Shapefile Request IDs list.
\nFuture Changes: A separate section under 'Study Zone Management' in the Portal to view details of Public Shapefiles.
\nThis section explains the process of uploading custom shapefiles.
\nThe system supports multiple formats including Google’s KML (Keyhole Markup Language), ESRI Shapefiles and GeoJson.
\nOur shapefile endpoint allows you to do the following:
\nOnce the shapefile has been accepted by the system, it will return a requestID. This requestID, once processed, along with the Study Zone names will be what you use to make the calls to the Count endpoints.
We can run a job through below two options:
\nInsights Developer Portal have the ability to test, explore all the API endpoints through Insights Developer Portal, by selecting a job type in Data Job tool.
\nYou can also edit an existing job and re-run it from View Data Jobs screen.
\nWe use a two part POST and GET method when making a call to our Endpoints. The POST request will validate the request and return a job ID, which should then be used to obtain the results via the GET request.
\nQueries are processed based on available computation space.
\nMost of the time, your results will be available on your first GET call. If it is not, it could be because your request is very large, or the server is busy. In this case, you may need to check the status of your request more than once. As a best practice, retry GET every 5 minutes.
The schema below shows a typical workflow for a study using the Location API. First, you will post your postRequest. Then you will post your getRequest to retrieve the status of your task.
\nThe data processing from the API calls are computed asynchronously. This means that you won't get the results of your call immediately. You will be returned a JobID, which represents the request you have made for the system.
\n{\n \"jobId\": \"84f4a1ba-a0d7-41d8-bc09-944440da6476\",\n \"link\": {\n \"rel\": \"dwelltime\",\n \"url\": \"/count/dwelltime/84f4a1ba-a0d7-41d8-bc09-944440da6476\"\n }\n}\n\n\nThere are multiple ways to POST a request to a REST API.
\nBest Practices:
\nTo find more information on what arguments to pass, please refer to the API's Reference section
\nTo get the status of your POST request, you need to send a request to the corresponding getRequest method using JobID generated during POST request for the respective API endpoint.
\n{\n \"requestId\": \"51a11295-2a94-40ac-82e5-29161faf9000\",\n \"study_zones\": [\n {\n \"geoid\": \"Kelowna\",\n \"buckets\": [\n {\n \"bucket\": \"2019-01-01T00:00:00\",\n \"0-15\": 35900\n }\n ]\n }\n ],\n \"bucket_size\": 1440,\n \"start_time\": \"2019-01-01T00:00:00\",\n \"end_time\": \"2019-01-02T00:00:00\"\n}\n\n\n{\n \"jobId\": \"84f4a1ba-a0d7-41d8-bc09-944440da6476\",\n \"status\": \"Processing\",\n \"link\": {\n \"rel\": \"dwelltime\",\n \"url\": \"/count/dwelltime/84f4a1ba-a0d7-41d8-bc09-944440da6476\"\n }\n}\n\n\nExclusion types are ways to segment the query down further to exclude / include certain types of devices based on segmentation such as demographic, identity, or other defined categories.
\nDestination end-point returns the count of devices with trips originating from each input study zone and terminating to each output study zone as specified by the input parameters.
\nStudy zone specified within the “input geo-id” is considered to be the Origin whereas the study zone specified within the “output geo-id” is considered to be the Destination.
\nFor a device to be qualified in the output, the trip must start (originate) and end (terminate) between the specified start and end times.
\nIn addition to the above, Destination end-point also provides an option to select pass-through study zones.
\nWith pass-through study zone(s) selected, Destination end-point will return the count of devices with trips originating from the study zone selected under input geo-id, passing through the study zones(s) selected pass-through geo-id and terminating to study zone selected under output geo-id.
\nIn case of multiple study zones selected under pass-through, the sequence of the trip will be determined based on the order in which the pass-through study zones have been selected.
\nConsider a scenarion wherein two study zones 'A' and 'B' have been selected under pass-through geo-id. The output would only contain the count of devices which travelled from Origin->A->B->Destination. Devices travelling through an alterate route from Origin to Destination for e.g., Origin->A->Destination or Origin->B->Destination or Origin->B->A->Destination will not be included in the output.
\nHow many devices travelled from Vancouver (Origin) to Burnaby (Destination) on May 1, 2022 between 9 AM and 1 PM.
\nHow many devices travelled from Vancouver (Origin) to Surrey (Destination) via Burnaby (Pass-through) on May 1, 2022 between 9 AM and 1 PM.
\nMinimum and Maximum Dwell Times can be specified independently for study zones within each group i.e. Origin, Destination and Pass-through study zones or can be specified globally which will be applied to all the study zones across all groups.
\nConsider a device traveling from Vancouver to Burnaby dwelled for 30 minutes in Vancouver as well as Burnaby.
\nIn this case, if the Minimum Dwell Time is set to anything in excess of 30 minutes, this device will be excluded from the output; similarly, if the Maximum Dwell Time is set to anything less than 30 minutes will also exclude this device from the output.
\nExclusion Types selected will remove the devices from the study area considered to the Destination.
\nConsider a resident device of Vancouver who traveled from Vancouver to Burnaby during the specified study period. In this case, excluding ‘Residents’ will exclude the device from the output.
\nDevices are bucketed based on when the trip originated from the study area considered to be the Origin.
\nConsider a case wherein the Start Time and End Time are specified as 9 AM and 1 PM respectively, and the Time Bucket Size is set to 120 minutes; output will be comprised of two buckets: Bucket 1 from 9 AM to 11 AM and Bucket 2 from 11 AM to 1 PM. Device traveling from Vancouver to Burnaby started from Vancouver at 10:30 AM reached Burnaby at 12:30 PM.
\nIn this case, the device will be forming a part of output under Bucket 1.
\nDemographic end-point provides the probabilistic demographic breakdown based on the census data of the Home Location of the devices that were available in the study zone specified under “input geo-id” and the input parameters.
\nFollowing are the topics available within the Demographic end-point which could be selected as an input parameter:
\nWhat is the age range wise percentage of people available in Vancouver on May 01, 2022 between 9 AM and 2 PM.
\nDwell Time end-point returns the unique number of devices available based on their dwell times in the input study zone as specified by the input parameters.
\nSimilar to Unique end-point, Dwell Time end-point analyzes each zone independently and hence contains only \"input geo-id\" as an input.
\nHow many devices spent between 30 to 90 minutes in Vancouver on May 1, 2022 between 9 AM and 1 PM.
\nMinimum and Maximum Dwell Times are applied to the study zone specified under \"input geo-id\".
\nNote: Specifying Maximum Dwell Time is mandatory for Dwell Time end-point.
\nConsider a device was available at Vancouver for 40 minutes during the specified study period.
\nIn this case, if the Minimum Dwell Time is set to anything in excess of 40 minutes irrespective of the Maximum Dwell Time specified, the device will be excluded from the output; similarly, if the Maximum Dwell Time is set to anything less than 40 minutes, this device will be excluded from the output.
\nDwell Time is calculated for each independent event and not cumulated for a device based on study period. Consider a case wherein device was available twice at Vancouver; initially from 9:00 AM to 9:30 AM (dwell time of 30 minutes) and then again from 12:15 to 1:05 PM (dwell time 50 minutes). Both these occurrences are considered to be two independent events.
\nIn this case, if the Maximum Dwell Time is set to 40 minutes, this device will be forming a part of the output due to the first event from 9 AM to 9:30 AM. In the second query, if the Minimum Dwell Time is set to 40 minutes and Maximum Dwell Time is set to 60 minutes, the same device will again be forming a part of the output, this time due to the second event from 12:15 PM to 1:05 PM.
\nIf the Minimum Dwell Time is set to 30 minutes and the Maximum Dwell Time is set to 60 minutes, there's a probability wherein both these events will be forming a part of the output which is further explained under Dwell Time Bucketing below.
\nDwell Time Bucket Size will bucket the devices based on their dwell times.
\nNote: Specifying Dwell Time Bucket Size is mandatory for Dwell Time end-point and the value cannot be more than the Maximum Dwell Time.
\nConsider a case wherein the Start Time and End Time are specified as 9 AM and 1 PM respectively, Minimum and Maximum Dwell Times are specified as 30 and 60 respectively and the Dwell Time Bucket is specified as 15; output will be comprised of two dwell buckets: Dwell Time Bucket 1 from 30 minutes to 45 minutes and Dwell Time Bucket 2 from 46 minutes to 60 minutes.
\nA device was available twice at Vancouver; initially from 9:00 AM to 9:30 AM (dwell time of 30 minutes) and then again from 12:15 PM to 1:05 PM (dwell time of 50 minutes). Both these occurrences are considered to be two independent events.
\nIn the above scenario, the same device will be forming a part of both the Dwell Time Buckets. Bucket 1 due to event 1 from 9:00 AM to 9:30 AM and under Bucket 2 due to event 2 from 12:15 PM to 1 PM.
\nDevices are bucketed based on their dwell start time in the study zone.
\nConsidering the same scenario mentioned under Dwell Time Bucketing section above with a Time Bucket Size of 120 minutes; the output will be comprised of 4 buckets (two time buckets and two dwell time buckets; one for each time bucket) as depicted wiht the help of a table below:
\nThe output will be as follows:
\nBased on Exclustion Type selected, devices will be identified and removed from the study area selected under \"inpute geo-id\".
\nConsider a scenario wherein Dwell Time Analysis is required to be conducted for the devices who are identified as Workers in Vancouver. In this case, excluding 'Non-Workers' will provide the required output.
\nThe Home end-point returns count of devices available in each input study zone broken-down by their corresponding Home Location as specified by the input parameters.
\nStudy zone specified within the \"input geo-id\" is considered to be the visiting location whereas the study zone specified within the \"output geo-id\" is considered to be the Home location.
\nAll the devices available in the visiting location between the specified start and end times will be qualified to be forming a part of the output.
\nHow many devices were at Burnaby (Visiting Location) on May 1, 2022 between 9 AM and 1 PM whose Home Location was Vancouver.
\nMinimum and Maximum Dwell Time is only applied to the study zone specified within the “input geo-id” i.e. the study zone considered to be the Visiting Location.
\nConsider a resident device of Vancouver was at Burnaby for 20 minutes during the specified study period.
\nIn this case, if the Minimum Dwell Time is set to anything in excess of 20 minutes, this device will be excluded from the output; similarly, if the Maximum Dwell Time is set to anything less than 20 minutes will also exclude this device from the output.
\nBased on the Exclusion Types selected, devices will be identified and removed from the study area considered to be the Visiting Location.
\nConsider a resident device of Vancouver who’s work location is Burnaby and was at Burnaby during the specified study period. In this case, excluding ‘Workers’ will exclude this device from the output.
\nDevices are bucketed based on their availability in the study zone considered to be the Visiting Location.
\nConsider a case wherein the Start Time and End Time are specified as 9 AM and 1 PM respectively, and the Time Bucket Size is set to 120 minutes; output will be comprised of two buckets: Bucket 1 from 9 AM to 11 AM and Bucket 2 from 11 AM to 1 PM. Resident device of Vancouver was available at Burnaby from 10 AM to 10:20 AM.
\nIn this case, this device will be forming a part of output under Bucket 1.
\nOD Matrix end-point performs travel analysis (people movement analysis) between two or more study areas. It provides the number of devices that traveled along with the total no. of trips between the matrix (selected study zones/areas) as specified by the input parameters.
\nAt least two study zones must be selected as a part of “input geo-id”.
\nNo. of devices traveled from Vancouver (Origin) to Burnaby (Destination) and vice versa i.e. no. of devices that traveled from Burnaby (Origin) to Vancouver (Destination) along with the total no. of trips on April 10 2022 between 9 AM and 1 PM.
\nMinimum and Maximum Dwell Times will be applied to both the study areas i.e. Origin as well as Destination.
\nConsider a device traveling from Vancouver to Burnaby dwelled for 15 minutes in Vancouver and 20 minutes in Burnaby.
\nIn this case, if Minimum Dwell Time is set to anything in excess of 20 minutes, this trip will be excluded from the output; similarly, if the Maximum Dwell Time is set to anything less than 15 minutes will also exclude this trip from the output.
\nExclusion Types selected will remove devices from the study area considered to be the Origin.
\nConsider a resident device of Vancouver who traveled from Vancouver to Burnaby and from Burnaby back to Vancouver.
\nIn this case, excluding ‘Residents’ will exclude this device while calculating the trips from Vancouver (considered as Origin) to Burnaby (considered as Destination) but will be considered in the output while calculating the trips from Burnaby (considered as Origin) to Vancouver (considered as Destination).
\nTrips are bucketed based on when the trip originated from the study area considered to be the Origin.
\nConsider a case wherein the Start Time and End Time are specified as 9 AM and 1 PM respectively, and the Time Bucket Size is set to 120 minutes; output will be comprised of two buckets: Bucket 1 from 9 AM to 11 AM and Bucket 2 from 11 AM to 1 PM. Device traveling from Vancouver to Burnaby started from Vancouver at 10:30 AM reached Burnaby at 12:30 PM.
\nIn this case, the trip will be forming a part of output under Bucket 1 for Origin: Vancouver and Destination: Burnaby.
\nOrigin end-point returns the count of devices with trips originating from each output study zone and terminating to each input study zone as specified by the input parameters.
\nStudy zone specified within the “input geo-id” is considered to be the Destination whereas the study zone specified within the “output geo-id” is considered to be the Origin.
\nFor a device to be qualified in the output, the trip must start (originate) and end (terminate) between the specified start and end times.
\nIn addition to the above, Origin end-point also provides an option to select pass-through study zones.
\nWith pass-through study zone(s) selected, Origin end-point will return the count of devices with trips originating from the study zone selected under output geo-id, passing through the study zones(s) selected pass-through geo-id and terminating to study zone selected under input geo-id.
\nIn case of multiple study zones selected under pass-through, the sequence of the trip will be determined based on the order in which the pass-through study zones have been selected.
\nConsider a scenarion wherein two study zones 'A' and 'B' have been selected under pass-through geo-id. The output would only contain the count of devices which travelled from Origin->A->B->Destination. Devices travelling through an alterate route from Origin to Destination for e.g., Origin->A->Destination or Origin->B->Destination or Origin->B->A->Destination will not be included in the output.
\nHow many devices traveled from Vancouver (Origin) to Burnaby (Destination) on May 1, 2022 between 9 AM and 1 PM.
\nHow many devices travelled from Vancouver (Origin) to Surrey (Destination) via Burnaby (Pass-through) on May 1, 2022 between 9 AM and 1 PM.
\nMinimum and Maximum Dwell Times can be specified independently for study zones within each group i.e. Origin, Destination and Pass-through study zones or can be specified globally which will be applied to all the study zones across all groups.
\nConsider a device traveling from Vancouver to Burnaby dwelled for 30 minutes in Vancouver as well as Burnaby.
\nIn this case, if the Minimum Dwell Time is set to anything in excess of 30 minutes, this device will be excluded from the output; similarly, if the Maximum Dwell Time is set to anything less than 30 minutes will also exclude this device from the output.
\nExclusion Types selected will remove devices from the study area considered to be the Destination.
\nConsider a resident device of Burnaby who traveled from Vancouver to Burnaby during the specified study period. In this case, excluding ‘Residents’ will exclude this device from the output.
\nDevices are bucketed based on when the trip terminated (i.e. reached the Destination study zone).
\nConsider a case wherein the Start time and End time are specified as 9 AM and 1 PM respectively, and the Time Bucket Size is set to 120 minutes; output will be comprised of two buckets: Bucket 1 from 9 AM to 11 AM and the Bucket 2 from 11 AM to 1 PM. Device traveling from Vancouver to Burnaby started from Vancouver at 10:30 AM reached Burnaby at 12:30 PM.
\nIn this case, this device will be forming a part of output under Bucket 2.
\nRepeat Visitation end-point returns the number of unique devices available in the study zone more than once based on specified by the input parameters.
\nRepeat Visitation end-point like Unique end-point analyzes each study zone independently and hence only contains “input geo-id” as an input.
\nAll the devices available in the study zone more than once i.e. has more than one independent event and each event between the specified start and end times will be qualified to be forming a part of the output. This is further explained under Dwell Time section below.
\nHow many devices went to Vancouver on May 1, 2022 more than once between 9 AM and 1 PM.
\nMinimum and Maximum Dwell Time is applied to the study zone specified within “input geo-id”.
\nConsider a case wherein a device was available twice at Vancouver; initially from 9:00 AM to 9:20 AM (dwell time 20 minutes) and then again from 12:15 PM to 1 PM (dwell time 45 minutes). Both these occurrences are considered to be two independent events and hence the device will be qualified to be forming a part of the output.
\nIn the above case, if Minimum Dwell Time is set to anything in excess of 20 minutes, the device will be excluded from the output; similarly, if the Maximum Dwell Time is set to anything less than 45 minutes will also exclude this device from the output.
\nDevices are bucketed based on their availability in the study zone.
\nConsider a case wherein the Start Time and End Time are specified as 9 AM and 1 PM respectively, and the Time Bucket Size is set to 120 minutes; output will be comprised of two buckets: Bucket 1 from 9 AM to 11 AM and Bucket 2 from 11 AM to 1 PM. Device was available at Vancouver from 9:30 AM to 10 AM and then again from 12:30 PM to 1 PM.
\nIn this case, this device will be forming a part of output under both of these buckets.
\nConsider a different scenario wherein a device was available at Vancouver from 9:30 AM to 10 AM and then again from 10:30 AM to 10:45 AM; in this case, the device will be forming a part of the output only under Bucket 1.
\nTotal Trip end-point returns the total number of trips made by devices to a study zone over a given period of time based on the input parameters.
\nSimilar to Unique and Repeat Visitation end-points, Total Trip end-point analyzes each study zone independently and hence contains only “input geo-id” as an input.
\nHow many trips did devices take to Vancouver on April 1, 2022 between 9 AM and 1 PM.
\nMinimum and Maximum Dwell Time is applied to the study zone specified within “input geo-id”.
\nConsider a device who took a trip to Vancouver was available at Vancouver for 20 minutes during the specified study period i.e. entered Vancouver at 9:00 AM and left Vancouver at 9:20 AM.
\nIn this case, if the Minimum Dwell Time is set to anything in excess of 20 minutes, the trip made by this device will be excluded from the output; similarly, if the Maximum Dwell Time is set to anything less than 20 minutes will also exclude the trip made by this device from the output.
\nDwell Time is calculated for each independent trip (event). Consider a case wherein a device took two trips to Vancouver during the specified study period; first trip/event from 9 AM to 9:20 AM (dwell time of 20 minutes) and the second trip/event from 12:15 PM to 1 PM (dwell time of 45 minutes).
\nIn this case, if the Maximum Dwell Time is set to 30 minutes, only the first trip will be forming a part of the output. In the second query, if the Minimum Dwell Time is set to 30 minutes, only the second trip will be forming a part of the output.
\nNow consider a case wherein Minimum Dwell Time is set to 15 minutes and Maximum Dwell Time is set to 60 minutes. In this case, both the trips will be included in the output.
\nBased on Exclusion Type selected, devices will be identified and removed from the study area selected under “input geo-id’.
\nConsider a resident device of Vancouver who travelled in and out of Vancouver multiple times during the specified study period. In this case, excluding ‘Residents’ will exclude all the trips made by this device from the output.
\nTrips are bucketed based on when the device entered the study zone.
\nConsider a case wherein the Start Time and End Time are specified as 9 AM and 1 PM respectively, and the Time Bucket Size is set to 120 minutes; output will be comprised of two Buckets: Bucket 1 from 9 AM to 11 AM and Bucket 2 from 11 AM to 1 PM. Device took a trip to Vancouver, entered Vancouver at 9 AM and left Vancouver at 12:30 PM.
\nIn this case, this trip will be forming a part of the output under Bucket 1.
\nA trade area is a geographic area from which a community/business generates the majority of its customers.
\nTrade Area end-point returns for each study zone selected in “output geo-id”, a list of classification (Primary/Secondary/Tertiary) for the study zone selected in “input geo-id”.
\nTrade Area defines where customers live (output geo-id) and how far they are likely to travel to a particular business district/area (input geo-id).
\nTrade Area is built using a weighted function that takes into account the following parameters to calculate a score between 0 and 1 for each of the study zones selected under output geo-id:
\n• Count Weight: is a 0 to 1 scale and represents how important the unique count is in classifying if the study zone is Primary, Secondary or Tertiary
• Trip Weight: is a 0 to 1 scale and represents how important total number of trips are in classifying if the study zone is Primary, Secondary or Tertiary
• Distance Weight: is a 0 to 1 scale and represents how important distance is in classifying if the study zone is Primary, Secondary and Tertiary
Primary and Secondary Threshold sets the bounds at which the equation will separate out the Primary, Secondary and Tertiary zones.
\nThe classification/category for a particular study zone selected under “output geo-id” is relative to the study zone selected under “input geo-id” and based upon the other study zones selected under “output geo-id”. If only one study zone is selected under “output geo-id”, Trade Area end-point will always return the category as ‘Primary’ as the score for one study zone will always be 1.
\nTrade Area end-point works best when the sum of Count Weight, Trip Weight and Distance Weight is 1.
\nConsider a scenario wherein 100 resident devices of Victoria and 300 resident devices of Vancouver were at business district Surrey between the study period selected. Classification of Victoria and Vancouver study zones for business district Surrey based on Count Weight 1, Primary Threshold 0.8 and Secondary Threshold 0.5 will be as follows:
\nConsider a scenario wherein a total of 150 trips were made by resident devices of Victoria and 800 trips were made by resident devices of Vancouver to business district Surrey between the study period selected. Classification of Victoria and Vancouver study zones for business district Surrey based on Count Weight 1, Primary Threshold 0.8 and Secondary Threshold 0.3 will be as follows:
\nUnique end-point returns the number of unique devices available in the input study zone based on the input parameters.
\nUnique end-point analyzes each study zone independently and hence only contains “input geo-id” as an input as compared to some of the other end-points like Home, OD matrix etc. wherein study zone specified as a part of “input geo-id” is analyzed based on it’s dependency on study zone specified as a part of “output geo-id”.
\nAll the devices available in the input study zone between the specified start and end times will be qualified to be forming a part of the output.
\nHow many unique devices visited Vancouver on May 1, 2022 between 9 AM and 1 PM.
\nMinimum and Maximum Dwell Times are applied to the study zone specified within “input geo-id”.
\nConsider a device was available at Vancouver for 20 minutes during the specified study period.
\nIn this case, if the Minimum Dwell Time is set to anything in excess of 20 minutes, this device will be excluded from the output; similarly, if the Maximum Dwell Time is set to anything less than 20 minutes will also exclude this device from the output.
\nDwell Time is calculated for each independent event and not cumulated for a device based on study period. Consider a case wherein a device was available twice at Vancouver; initially from 9:00 AM to 9:20 AM (dwell time 20 minutes) and then again from 12:15 PM to 1 PM (dwell time 45 minutes). Both these occurrences are considered to be two independent events.
\nIn this case, if the Maximum Dwell Time is set to 30 minutes, this device will be forming a part of the output due to the first event from 9 AM to 9:20 AM. In the second query, if the Minimum Dwell Time is set to 30 minutes, the same device will again be forming a part of the output, this time due to the second event from 12:15 PM to 1 PM.
\nFor further clarification, Unique end-point returns number of unique devices and not the number of unique events and hence, even if a device has two independent events and they both qualify to be forming a part of the output based on specified input parameters, the device will only be counted once in the output.
\nConsider a case wherein the Minimum Dwell Time is set to 15 minutes and Maximum Dwell
Time is set to 60 minutes. In this case, both the events mentioned above are eligible to be forming a part of the output, but this device will only be considered once in the output.
Devices are bucketed based on their availability in the study zone.
\nConsider a case wherein the Start Time and End Time are specified as 9 AM and 1 PM respectively, and the Time Bucket Size is set to 120 minutes; output will be comprised of two buckets: Bucket 1 from 9 AM to 11 AM and Bucket 2 from 11 AM to 1 PM. Device was available at Vancouver from 9:30 AM to 12:30 PM.
In this case, this device will be forming a part of output under both of these buckets.
Consider a different scenario wherein a device was available at Vancouver only from 9:30 AM to 10 AM; in this case, the device will be forming a part of the output only under Bucket 1.
\nThe Work end-point returns count of devices available in each input study zone broken-down by their corresponding Work Location as specified by the input parameters.
\nStudy zone specified within the \"input geo-id\" is considered to be the Visiting Location whereas the study zone specified within the \"output geo-id\" is considered to be the Work Location.
\nAll the devices available in the visiting location between the specified start and end times will be qualified to be forming a part of the output.
\nHow many devices were at Burnaby (Visiting Location) on May 1, 2022 between 9 AM and 1 PM whose Work Location was Vancouver.
\nMinimum and Maximum Dwell Time is only applied to the study zone specified within the “input geo-id” i.e. study zone considered to be the Visiting Location.
\nConsider a resident device of Vancouver was at Burnaby for 20 minutes during the specified study period.
\nIn this case, if the Minimum Dwell Time is set to anything in excess of 20 minutes, this device will be excluded from the output; similarly, if the Maximum Dwell Time is set to anything less than 20 minutes will also exclude this device from the output.
\nBased on the Exclusion Types selected, devices will be identified and removed from the study area considered to be the Visiting Location.
\nConsider a device who’s work location is Vancouver and is a resident device of Burnaby and was at Burnaby during the specified study period. In this case, excluding ‘Residents’ will exclude this device from the output.
\nDevices are bucketed based on their availability in the study zone considered to be the Visiting Location.
\nConsider a case wherein the Start Time and End Time are specified as 9 AM and 1 PM respectively, and the Time Bucket Size is set to 120 minutes; output will be comprised of two buckets: Bucket 1 from 9 AM to 11 AM and Bucket 2 from 11 AM to 1 PM. Device, who’s work location is Vancouver was available at Burnaby from 10 AM to 10:20 AM.
\nIn this case, this device will be forming a part of output under Bucket 1.
\nhttpsWe have developed the following API services to help customers utilize TELUS Geo-intelligence data assets and help answer a range of questions around location and movement patterns within Canada.
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\nExample: What is the count of devices split by age range that were at Trinity Bellwoods area between 1st January 2020 and 15th January 2020?
\n","urlObject":{"path":["count","demographic"],"host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"query":[],"variable":[]}},"response":[{"id":"be80067c-4e3b-4ee6-842e-a59abd86d3ee","name":"Job created for request","originalRequest":{"method":"POST","header":[{"description":"Added as a part of security scheme: oauth2","key":"Authorization","value":"(Required) CustomerId is required
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\nExample: How many devices went to Port Credit coming from Brampton on a daily basis between 15th - 18th January 2020
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\n","urlObject":{"path":["geofence"],"host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"query":[],"variable":[]}},"response":[{"id":"8ad0021f-c385-46b3-9745-874ebfdd4da9","name":"response","originalRequest":{"method":"GET","header":[{"description":"Added as a part of security scheme: oauth2","key":"Authorization","value":"Get list of polygons from uploaded shapefiles
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\n","key":"customerId","value":"velit tempor"},{"key":"Content-Type","value":"application/json"},{"key":"Accept","value":"application/json"}],"body":{"mode":"raw","raw":"{\n \"input_geoid\": {\n \"requestId\": \"c764703b-2043-48ff-8929-d18bc50f1a62\",\n \"study_zone\": [\n \"Kelowna\",\n \"Toronto\"\n ]\n },\n \"start_time\": \"2020-01-03T00:00:00\",\n \"end_time\": \"2020-01-03T01:00:00\",\n \"output_geoid\": {\n \"requestId\": \"bd8b10da-8318-4fc1-baed-5823e14b2c52\",\n \"study_zone\": [\n \"Calgary\",\n \"Niagara\"\n ]\n },\n \"estimation_only\": false,\n \"time_bucket_size\": 30,\n \"max_dwell_time\": 30,\n \"min_dwell_time\": 15\n}","options":{"raw":{"language":"json"}}},"url":"https://location-api.insights.telus.com/product/insightsRequest/v1/count/home","description":"The Home endpoint helps us to understand the Home location of those that are visiting a particular location.
\nFor each study zone that is specified within the input “geo-id”, what are the home locations of the people there.
\nThe home locations are grouped by the output study zones which must be specified as part of the GET request, within the “output-geoid” parameter
\nExample: For everyone in Whistler on Saturday 31st May 2020, how many of the device's home location is in Squamish.
\n","urlObject":{"path":["count","home"],"host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"query":[],"variable":[]}},"response":[{"id":"e7d86c24-20ef-4279-91ad-bf9d96f40626","name":"Job created for request","originalRequest":{"method":"POST","header":[{"description":"Added as a part of security scheme: oauth2","key":"Authorization","value":"(Required) CustomerId is required
\n","key":"customerId","value":"velit tempor"},{"key":"Accept","value":"application/json"}],"url":"https://location-api.insights.telus.com/product/insightsRequest/v1/count/home/:jobId","description":"Get count of people who are in the zone based on home location
\n","urlObject":{"path":["count","home",":jobId"],"host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"query":[],"variable":[{"id":"c2d02af5-9a9e-4209-811b-dde30affe4fd","description":{"content":"(Required) The request id returned from POST request
\n","type":"text/plain"},"type":"any","value":"velit tempor","key":"jobId"}]}},"response":[{"id":"06510cac-8e73-4f8f-9c93-f3a5fad92262","name":"response","originalRequest":{"method":"GET","header":[{"description":"Added as a part of security scheme: oauth2","key":"Authorization","value":"Get count of people in Current(Input) location who have Home in provided(Output) location
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\n","urlObject":{"path":["job",":jobid"],"host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"query":[],"variable":[{"id":"1e08d5ca-b608-4f57-8ebb-1183bd8c55f4","type":"any","key":"jobid"}]}},"response":[{"id":"fe32a75e-f2cb-4d60-a87c-74a5ab510f62","name":"response","originalRequest":{"method":"DELETE","header":[{"description":"Added as a part of security scheme: oauth2","key":"Authorization","value":"(Required)
\n","key":"customerid","value":"velit tempor"},{"key":"Accept","value":"*/*"}],"url":"https://location-api.insights.telus.com/product/insightsRequest/v1/job/:jobid/cancel?jobid=velit tempor","description":"Cancel a running job. You will be able to edit and resubmit if you ran something by mistake.
\n","urlObject":{"path":["job",":jobid","cancel"],"host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"query":[{"description":{"content":"(Required)
\n","type":"text/plain"},"key":"jobid","value":"velit tempor"}],"variable":[{"id":"3e04af99-f17a-492c-8897-35749a0474a0","type":"any","key":"jobid"}]}},"response":[{"id":"1f73b7be-7b74-43f7-8270-00491328a97b","name":"response","originalRequest":{"method":"PATCH","header":[{"description":"Added as a part of security scheme: oauth2","key":"Authorization","value":"This endpoint returns the active jobs irrespective of the status of the job based on the following query parameters.
\n","urlObject":{"path":["job"],"host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"query":[{"key":"limit","value":"5"},{"key":"offset","value":"0"},{"key":"sort","value":"-createdDate"},{"key":"selectjobs","value":"user"}],"variable":[]}},"response":[{"id":"353123ad-c3cc-445f-a968-ae0e4cf2bf93","name":"Success - Paginated list of jobs","originalRequest":{"method":"GET","header":[{"key":"customerId","value":"velit tempor","type":"text"}],"url":{"raw":"https://location-api.insights.telus.com/product/insightsRequest/v1/job?limit=5&offset=0&sort=-createdDate","protocol":"https","host":["location-api","insights","telus","com"],"path":["product","insightsRequest","v1","job"],"query":[{"key":"limit","value":"5"},{"key":"offset","value":"0"},{"key":"sort","value":"-createdDate"}]}},"status":"Partial Content","code":206,"_postman_previewlanguage":"json","header":[{"key":"Content-Type","name":"Content-Type","value":"application/json","description":"","type":"text"}],"cookie":[],"responseTime":null,"body":"{\n \"_metadata\": {\n \"page\": 1,\n \"per_page\": 5,\n \"page_count\": 5,\n \"total_count\": 16,\n \"range\": \"1-5/16\",\n \"links\": [\n {\n \"self\": \"/job?limit=5&offset=0&sort=-createdDate\"\n },\n {\n \"first\": \"/job?limit=5&offset=0&sort=-createdDate\"\n },\n {\n \"last\": \"/job?limit=5&offset=15&sort=-createdDate\"\n },\n {\n \"next\": \"/job?limit=5&offset=5&sort=-createdDate\"\n }\n ]\n },\n \"records\": [\n {\n \"jobId\": \"velit tempor1\",\n \"api\": \"demographic\",\n \"status\": \"COMPLETE\",\n \"queryParams\": {\n \"end_time\": \"2020-10-04T23:59:59\",\n \"input_geoid\": {\n \"study_zone\": [\n \"Downtown\",\n \"Inkster\",\n \"Seven Oaks\",\n \"River Heights\",\n \"Point Douglas\",\n \"Transcona\",\n \"St. Boniface\",\n \"River East\",\n \"St. Vital\",\n \"Fort Garry\",\n \"Assiniboine South\",\n \"St. James - Assiniboia\"\n ],\n \"requestId\": \"shape-file-zip-12150800-8b49a4acbc1d\"\n },\n \"time_bucket_size\": 1440,\n \"api\": \"demographic\",\n \"topics\": [\n {\n \"topic\": \"Marital status\"\n },\n {\n \"topic\": \"Age characteristics\"\n },\n {\n \"topic\": \"First official language spoken\"\n },\n {\n \"topic\": \"Family characteristics-Family size\"\n },\n {\n \"topic\": \"Household and dwelling characteristics-household size\"\n },\n {\n \"topic\": \"Income of households in 2015-Household total income groups in 2015 for private households\"\n }\n ],\n \"start_time\": \"2020-10-04T00:00:00\"\n },\n \"created_date\": \"2022-10-31T11:27:59\"\n },\n {\n \"jobId\": \"velit tempor2\",\n \"api\": \"demographic\",\n \"status\": \"COMPLETE\",\n \"queryParams\": {\n \"start_time\": \"2020-10-04T00:00:00\",\n \"api\": \"demographic\",\n \"time_bucket_size\": 1440,\n \"end_time\": \"2020-10-04T23:59:59\",\n \"topics\": [],\n \"input_geoid\": {\n \"requestId\": \"shape-file-zip-12150800-8b49a4acbc1d\",\n \"study_zone\": [\n \"Downtown\",\n \"Inkster\",\n \"Seven Oaks\",\n \"River Heights\",\n \"Point Douglas\",\n \"Transcona\",\n \"St. Boniface\",\n \"River East\",\n \"St. Vital\",\n \"Fort Garry\",\n \"Assiniboine South\",\n \"St. James - Assiniboia\"\n ]\n }\n },\n \"created_date\": \"2022-10-31T11:26:46\"\n },\n {\n \"jobId\": \"velit tempor3\",\n \"api\": \"demographic\",\n \"status\": \"COMPLETE\",\n \"queryParams\": {\n \"end_time\": \"2020-10-04T23:59:59\",\n \"topics\": [],\n \"time_bucket_size\": 1440,\n \"api\": \"demographic\",\n \"start_time\": \"2020-10-04T00:00:00\",\n \"input_geoid\": {\n \"requestId\": \"shape-file-zip-12150800-8b49a4acbc1d\",\n \"study_zone\": [\n \"Downtown\",\n \"Inkster\",\n \"Seven Oaks\",\n \"River Heights\",\n \"Point Douglas\",\n \"Transcona\",\n \"St. Boniface\",\n \"River East\",\n \"St. Vital\",\n \"Fort Garry\",\n \"Assiniboine South\",\n \"St. James - Assiniboia\"\n ]\n }\n },\n \"created_date\": \"2022-10-31T11:22:51\"\n },\n {\n \"jobId\": \"velit tempor4\",\n \"api\": \"repeatvisitation\",\n \"status\": \"COMPLETE\",\n \"queryParams\": {\n \"time_bucket_size\": 1440,\n \"end_time\": \"2020-10-04T23:59:59\",\n \"min_dwell_time\": 15,\n \"input_geoid\": {\n \"study_zone\": [\n \"Downtown\",\n \"Inkster\",\n \"Seven Oaks\",\n \"River Heights\",\n \"Point Douglas\",\n \"Transcona\",\n \"St. Boniface\",\n \"River East\",\n \"St. Vital\",\n \"Fort Garry\",\n \"Assiniboine South\",\n \"St. James - Assiniboia\"\n ],\n \"requestId\": \"shape-file-zip-12150800-8b49a4acbc1d\"\n },\n \"api\": \"repeatvisitation\",\n \"start_time\": \"2020-10-04T00:00:00\"\n },\n \"created_date\": \"2022-10-31T07:28:08\"\n },\n {\n \"jobId\": \"velit tempor5\",\n \"api\": \"repeatvisitation\",\n \"status\": \"COMPLETE\",\n \"queryParams\": {\n \"input_geoid\": {\n \"requestId\": \"shape-file-zip-12150800-8b49a4acbc1d\",\n \"study_zone\": [\n \"Downtown\",\n \"Inkster\",\n \"Seven Oaks\",\n \"River Heights\",\n \"Point Douglas\",\n \"Transcona\",\n \"St. Boniface\",\n \"River East\",\n \"St. Vital\",\n \"Fort Garry\",\n \"Assiniboine South\",\n \"St. James - Assiniboia\"\n ]\n },\n \"api\": \"repeatvisitation\",\n \"start_time\": \"2020-10-04T00:00:00\",\n \"end_time\": \"2020-10-04T23:59:59\",\n \"time_bucket_size\": 1440\n },\n \"created_date\": \"2022-10-31T07:23:08\"\n }\n ]\n}"},{"id":"54ed74e0-da2a-402e-a6aa-d73aa351e519","name":"Unauthorized","originalRequest":{"method":"GET","header":[{"key":"customerId","value":"velit tempor","type":"text"}],"url":{"raw":"https://location-api.insights.telus.com/product/insightsRequest/v1/job?limit=5&offset=0&sort=-createdDate","host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"path":["job"],"query":[{"key":"limit","value":"5"},{"key":"offset","value":"0"},{"key":"sort","value":"-createdDate"}]}},"status":"Unauthorized","code":401,"_postman_previewlanguage":"json","header":[{"key":"Content-Type","name":"Content-Type","value":"application/json","description":"","type":"text"}],"cookie":[],"responseTime":null,"body":"{\n \"code\": 401,\n \"message\": \"Unauthorized\"\n}"}],"_postman_id":"1ade3e9e-af2f-4450-b914-3a3088d6f0db"}],"id":"a99a8865-4e85-448f-8a15-5f572e939685","_postman_id":"a99a8865-4e85-448f-8a15-5f572e939685","description":"","auth":{"type":"oauth2","oauth2":{"basicConfig":[]},"isInherited":true,"source":{"_postman_id":"d8e042de-3754-42b6-beb6-a174697eddf8","id":"d8e042de-3754-42b6-beb6-a174697eddf8","name":"Telus Insights Location API","type":"collection"}}},{"name":"ODMatrix","item":[{"name":"post OD Matrix","id":"c7013e58-60b0-4c72-943e-e1f10bb22b7d","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"auth":{"type":"oauth2","oauth2":{"basicConfig":[],"advancedConfig":[{"key":"scope","value":"814"},{"key":"clientSecret","value":"•••••••"},{"key":"clientId","value":"•••••••"},{"key":"accessTokenUrl","value":"https://apigw-pr.telus.com/token"},{"key":"grant_type","value":"(Required) CustomerId is required
\n","key":"customerId","value":"velit tempor"},{"key":"Content-Type","value":"application/json"},{"key":"Accept","value":"application/json"}],"body":{"mode":"raw","raw":"{\n \"input_geoid\": {\n \"requestId\": \"c764703b-2043-48ff-8929-d18bc50f1a62\",\n \"study_zone\": [\n \"Kelowna\",\n \"Toronto\"\n ]\n },\n \"timezone\": \"UTC\",\n \"start_time\": \"2020-01-03T00:00:00\",\n \"end_time\": \"2020-01-03T01:00:00\",\n \"estimation_only\": false,\n \"time_bucket_size\": 30,\n \"min_dwell_time\": 15,\n \"max_dwell_time\": 30\n}","options":{"raw":{"language":"json"}}},"url":"https://location-api.insights.telus.com/product/insightsRequest/v1/count/odmatrix","description":"An OD Matrix is an area of study between two or more areas as defined by the study areas. \nIt will provide the number of devices that travelled between the Matrix defined based upon the study zones and parameters provided in the job for the corresponding Job ID
\nExample:\nHow many devices travelled between Toronto and Kingston (and vice versa) between Mon 20th April - Fri 24th April between 6am and 8pm.
\n","urlObject":{"path":["count","odmatrix"],"host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"query":[],"variable":[]}},"response":[{"id":"b7647ca5-480d-4523-b629-76ea9670804f","name":"Job created for request","originalRequest":{"method":"POST","header":[{"description":"Added as a part of security scheme: oauth2","key":"Authorization","value":"(Required) CustomerId is required
\n","key":"customerId","value":"velit tempor"},{"key":"Accept","value":"application/json"}],"url":"https://location-api.insights.telus.com/product/insightsRequest/v1/count/odmatrix/:jobId","description":"","urlObject":{"path":["count","odmatrix",":jobId"],"host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"query":[],"variable":[{"id":"a7b9306d-480a-48ec-909f-dd5be8b2f5b2","description":{"content":"(Required) The request id returned from POST request
\n","type":"text/plain"},"type":"any","value":"velit tempor","key":"jobId"}]}},"response":[{"id":"67003eec-dced-4c64-a4d9-7b611dbe0f96","name":"response","originalRequest":{"method":"GET","header":[{"description":"Added as a part of security scheme: oauth2","key":"Authorization","value":"Get the OD Matrix with the count of trips going from each origin to each destination
\n","_postman_id":"d9b531ea-822a-4f94-8c73-fee1ea42b14c","auth":{"type":"oauth2","oauth2":{"basicConfig":[]},"isInherited":true,"source":{"_postman_id":"d8e042de-3754-42b6-beb6-a174697eddf8","id":"d8e042de-3754-42b6-beb6-a174697eddf8","name":"Telus Insights Location API","type":"collection"}}},{"name":"Origin","item":[{"name":"post Origin","id":"1ed5c6ef-f4d1-4422-a136-a91a6a1d8db7","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"auth":{"type":"oauth2","oauth2":{"basicConfig":[],"advancedConfig":[{"key":"scope","value":"814"},{"key":"clientSecret","value":"•••••••"},{"key":"clientId","value":"•••••••"},{"key":"accessTokenUrl","value":"https://apigw-pr.telus.com/token"},{"key":"grant_type","value":"(Required) CustomerId is required
\n","key":"customerId","value":"velit tempor"},{"key":"Content-Type","value":"application/json"},{"key":"Accept","value":"application/json"}],"body":{"mode":"raw","raw":"{\n \"input_geoid\": {\n \"requestId\": \"c764703b-2043-48ff-8929-d18bc50f1a62\",\n \"study_zone\": [\n \"Kelowna\",\n \"Toronto\"\n ],\n \"min_dwell_time\": 15,\n \"max_dwell_time\": 30\n },\n \"pass_through_geoid\": {\n \"requestId\": \"a7643453703b-23443-4834f-8359-8c50f1a\",\n \"study_zone\": [\n \"Seven Oaks\"\n ],\n \"min_dwell_time\": 15,\n \"max_dwell_time\": 30\n },\n \"output_geoid\": {\n \"requestId\": \"bd8b10da-8318-4fc1-baed-5823e14b2c52\",\n \"study_zone\": [\n \"Calgary\",\n \"Niagara\"\n ],\n \"min_dwell_time\": 15,\n \"max_dwell_time\": 30\n },\n \"timezone\": \"UTC\",\n \"start_time\": \"2020-01-03T00:00:00\",\n \"end_time\": \"2020-01-03T01:00:00\",\n \"time_bucket_size\": 30,\n \"min_dwell_time\": 15,\n \"max_dwell_time\": 30\n}","options":{"raw":{"language":"json"}}},"url":"https://location-api.insights.telus.com/product/insightsRequest/v1/count/origin","description":"Provides the number of devices with trips originating at each output study zone for the given parameters defined by the job, which corresponds to the job ID.
\nExample: How many devices came from Port Credit, and Brampton and travelled to Rogers Centre in downtown Toronto on 1st December 2019, between 9am - 1pm.
\n","urlObject":{"path":["count","origin"],"host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"query":[],"variable":[]}},"response":[{"id":"5e615554-6852-4534-a3ee-9484ac4fc036","name":"Job created for request","originalRequest":{"method":"POST","header":[{"description":"Added as a part of security scheme: oauth2","key":"Authorization","value":"(Required) CustomerId is required
\n","key":"customerId","value":"velit tempor"},{"key":"Accept","value":"application/json"}],"url":"https://location-api.insights.telus.com/product/insightsRequest/v1/count/origin/:jobId","description":"","urlObject":{"path":["count","origin",":jobId"],"host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"query":[],"variable":[{"id":"539dd686-e104-4eb2-99aa-9a7498eace70","description":{"content":"(Required) The request id returned from POST request
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\n","_postman_id":"32b08a9f-6ca3-4862-b4f3-49204b427782","auth":{"type":"oauth2","oauth2":{"basicConfig":[]},"isInherited":true,"source":{"_postman_id":"d8e042de-3754-42b6-beb6-a174697eddf8","id":"d8e042de-3754-42b6-beb6-a174697eddf8","name":"Telus Insights Location API","type":"collection"}}},{"name":"Read Area","item":[{"name":"List Shapefiles","id":"e05984ba-917a-4c7a-92cb-fff5e0e628f2","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"auth":{"type":"oauth2","oauth2":{"basicConfig":[]},"isInherited":false},"method":"GET","header":[{"key":"customerId","value":"velit tempor","type":"text"}],"url":"https://location-api.insights.telus.com/product/insightsRequest/v1/shapefile?selectfiles=user","description":"This endpoint returns the list of shapefiles based on the following query parameters.
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\n","type":"text/plain"},"key":"selectfiles","value":"user"}],"variable":[]}},"response":[{"id":"3891000a-5390-48c3-a3bb-8cae7bd2c0b1","name":"Success - list of user shapefiles","originalRequest":{"method":"GET","header":[{"key":"customerId","value":"velit tempor","type":"text"}],"url":{"raw":"https://location-api.insights.telus.com/product/insightsRequest/v1/shapefile?selectfiles=user","protocol":"https","host":["location-api","insights","telus","com"],"path":["product","insightsRequest","v1","shapefile"],"query":[{"key":"selectfiles","value":"user"}]}},"status":"Partial Content","code":206,"_postman_previewlanguage":"json","header":[{"key":"Content-Type","name":"Content-Type","value":"application/json","description":"","type":"text"}],"cookie":[],"responseTime":null,"body":"[\n {\n \"orginalFilename\": \"winnepeg.zip\",\n \"status\": \"COMPLETE\",\n \"requestId\": \"winnepeg-zip-2aaaee62-bc47-4cb9-a388-1d88aa5386fc\",\n \"totalZones\": 1,\n \"studyZones\": [\n \"zone 1\"\n ],\n \"createdDate\": \"2022-09-20T23:14:21\",\n \"shapeFileType\": \"user\"\n }\n]"},{"id":"abd9aa7b-4ac4-4690-b44c-904476963f19","name":"Unauthorized","originalRequest":{"method":"GET","header":[{"key":"customerId","value":"velit tempor","type":"text"}],"url":{"raw":"https://location-api.insights.telus.com/product/insightsRequest/v1/shapefile?selectfiles=user","host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"path":["shapefile"],"query":[{"key":"selectfiles","value":"user"}]}},"status":"Unauthorized","code":401,"_postman_previewlanguage":"json","header":[{"key":"Content-Type","name":"Content-Type","value":"application/json","description":"","type":"text"}],"cookie":[],"responseTime":null,"body":"{\n \"code\": 401,\n \"message\": \"Unauthorized\"\n}"}],"_postman_id":"e05984ba-917a-4c7a-92cb-fff5e0e628f2"},{"name":"Retrieve status of the shapefile upload","id":"b10ad9bf-e584-4cd7-9080-437e8dae8a11","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"auth":{"type":"oauth2","oauth2":{"basicConfig":[],"advancedConfig":[{"key":"scope","value":"814"},{"key":"clientSecret","value":"•••••••"},{"key":"clientId","value":"•••••••"},{"key":"accessTokenUrl","value":"https://apigw-pr.telus.com/token"},{"key":"grant_type","value":"(Required) CustomerId is required
\n","key":"customerId","value":"velit tempor"},{"key":"Accept","value":"application/json"}],"url":"https://location-api.insights.telus.com/product/insightsRequest/v1/shapefile/:requestId","description":"By passing in the request ID, you can determine the status of the shapefile
\n","urlObject":{"path":["shapefile",":requestId"],"host":["https://location-api.insights.telus.com/product/insightsRequest/v1"],"query":[],"variable":[{"id":"22f52008-8cd4-4f0d-82fd-28a0c785d058","description":{"content":"(Required) Request ID generated from POST /upload
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