Requesting Raw Data¶

Navixy Data Warehouse API allows telematics solution providers and developers of location-based solutions to access comprehensive, unprocessed data from tracking devices. This enables accurate information retrieval and a deeper understanding of collected data, facilitating issue resolution and integration into other systems for extensive analysis and business use.

Typical Use Case¶

For efficient fuel management, especially in fleet management or cargo transportation, integrating your ERP system with the Navixy platform is essential. This integration allows you to seamlessly request raw fuel data from specific devices, enhancing your fuel monitoring and expense tracking capabilities.

Imagine that you need to retrieve the following data:

• Fuel Level
• Device Location
• Mileage (Odometer)
• Speed
• Date and Time
• Any other data valuable to your business

Please note that you will not receive human-readable information about fuel drains and refills, excessive consumption, idling, and other analytics—those are available through backend-API methods. Raw data requests provide unprocessed data received directly from the device, decoded by the Navixy platform, offering instantaneous data readings for a specific period. This data is suitable for further processing and analysis on your end.

Requesting Inputs List¶

Tracking devices from different manufacturers have different specifics of work and send data in various forms. In addition, sensors can be of different types: digital and analog, wired and wireless, built-in and external. Also, there can be several sensors monitoring the same type of readings: for example, two fuel sensors in two tanks, internal and external temperature sensors, etc.

Before requesting raw data, we need to understand what data the device can report to the platform and what the data inputs are named. To do this, we need to use the raw_data/get_inputs request.

Example for a device with ID 123456:

curl -X 'POST' \
'https://api.eu.navixy.com/dwh/v1/tracker/raw_data/get_inputs' \
-H 'Content-Type: application/json' \
-d '{
  "hash": "6dc7d304dec4434f4c4202ec42817f83",
  "tracker_id": 123456
}'

The platform will notify us about success, and we will see the following JSON object in response:

{
  "discrete_inputs": 2,
  "discrete_outputs": 1,
  "inputs": [
    "analog_1",
    "battery_voltage",
    "board_voltage",
    "ext_temp_sensor_4",
    "freq_1",
    "hw_mileage",
    "impulse_counter_1",
    "lls_level_4",
    "lls_temperature_4"
  ],
  "states": [
    "hardware_key"
  ],
  "success": true
}

Among the obtained inputs, we see the one of interest to us - lls_level_4. This is a fuel level input, and the index 4 indicates the value is a range of LLS levels from 1 to 4. This means the device can send fuel data on a maximum of four inputs: from lls_level_1 to lls_level_4.

We also see the hw_mileage, which will allow us to get the value of the hardware odometer.

Requesting Raw Data Readings¶

Now we know the names of the inputs where the fuel data comes from, and we can use them in the API query. However, we also need other parameters for more accurate analysis. This data is not related to sensors, so the above query does not return it. They come in simple columns and are listed on the appropriate documentation page.

We will use the following columns:

• lat
• lng
• speed

In addition, we will use names for inputs according to the information obtained earlier:

• inputs.lls_level_1
• inputs.hw_mileage

The API request raw_data/read for reading the required raw data in our case should look like this:

curl -X 'POST' \
'https://api.eu.navixy.com/dwh/v1/tracker/raw_data/read' \
-H 'accept: text/csv' \
-H 'Content-Type: application/json' \
-d '{
  "hash": "6dc7d304dec4434f4c4202ec42817f83",
  "tracker_id": "123456",
  "from": "2023-11-29T08:31:00Z",
  "to": "2023-11-29T08:32:00Z",
  "columns": [
    "lat",
    "lng",
    "speed",
    "inputs.lls_level_1",
    "inputs.hw_mileage"
  ]
}'

The response is returned in a CSV table format:

"msg_time","lat","lng","speed","inputs.lls_level_1","inputs.hw_mileage"
"2023-11-29T08:31:10Z",54.2312716,69.5261833,0,3307,24250.798
"2023-11-29T08:31:12Z",54.1811183,69.5331349,24,3274,24257.16
"2023-11-29T08:31:27Z",54.1802066,69.5333599,21,\N,\N
"2023-11-29T08:31:27Z",54.1802066,69.5333599,21,3274,24257.262
"2023-11-29T08:31:30Z",54.180055,69.533395,20,3274,24257.279
"2023-11-29T08:31:31Z",54.180005,69.5334083,20,3274,24257.285
"2023-11-29T08:31:33Z",54.179915,69.5334266,17,3274,24257.295
"2023-11-29T08:31:34Z",54.1798766,69.533435,15,3274,24257.299
"2023-11-29T08:31:36Z",54.1798116,69.5334433,12,3274,24257.306
"2023-11-29T08:31:37Z",54.179785,69.5334416,10,3274,24257.309
"2023-11-29T08:31:39Z",54.1797366,69.533425,9,3274,24257.315
"2023-11-29T08:31:40Z",54.1797183,69.5334083,8,3274,24257.315
"2023-11-29T08:31:42Z",54.1796883,69.5333449,10,3274,24257.322
"2023-11-29T08:31:43Z",54.17968,69.5333016,12,3274,24257.325
"2023-11-29T08:31:45Z",54.1796816,69.53318,15,3274,24257.333
"2023-11-29T08:31:47Z",54.1796816,69.533025,20,3274,24257.343

In the above example, we see the output for one minute of tracking. When querying raw data over a long period of time, the response can reach significant sizes — this must be considered.

The above example is one of the simplest, but it clearly demonstrates the process of using an API request to read raw data. You can query a lot of data at once and over large periods of time, depending on your objectives.

Specifying Time Frame¶

When requesting raw data, you must specify the exact period for which you need the data to ensure the platform can accurately process your request and return the necessary information.

Similar to the Backend API, you can specify the date and time in either the standard YYYY-MM-DD HH:mm:ss format with or without a time zone or in ISO 8601 format.

The default format for Data Warehouse API requests is ISO 8601.

The platform allows you to request raw data for any period within the time frame limits.

All methods for specifying the date and time provided below are equally valid. Choose the one that is most convenient or best matches the format used in your integrations.

ISO 8601¶

ISO 8601 is an international standard for representing date and time-related data in an unambiguous form that is both human- and machine-readable. However, some programs, including Microsoft Excel, may not be able to read such timestamps, so its use is optional.

Using this date/time standard when requesting raw data, you can specify the exact time for which you need the data, as well as the time zone - not only as in the user account or UTC+0, but any other time zone of your choice, if required.

According to ISO 8601, the date and time are represented starting with the year, followed by month, day, hour, minutes, seconds, milliseconds, and time zone offset.

Date and time format:

[yyyy]-[mm]-[dd]T[hh]:[mm]:[ss]±[offset]

Time zone offset can be specified using any of the following formats:

• +-HH:mm - for example, -06:00 or +05:30.
• +-HHmm - for example, -0500 or +0100.
• +-HH - for example, -03 or +07.
• Z - no offset (UTC+0).

Timestamp examples:

Let's assume that the client account is set to UTC+4 (Dubai) time, and the time we need is 10:20 AM, the date is December 2, 2023. Then we can specify the timestamp in one of the following ways:

• 2023-12-02T10:20:00+04:00
• 2023-12-02T10:20:00+04
• 2023-12-02T06:20:00Z (converted to UTC+0)

Another example. The client account is set to UTC-6 (Mexico) time, and the time we need is 10:55 PM, the date is December 11, 2023. Then we can specify the timestamp in one of the following ways:

• 2023-12-11T23:55:00-06:00
• 2023-12-11T23:55:00-06
• 2023-12-12T04:55:00Z (converted to UTC+0, mind the date)

API request example:

curl -X 'POST' \
'https://api.eu.navixy.com/dwh/v1/tracker/raw_data/read' \
-H 'accept: text/csv' \
-H 'Content-Type: application/json' \
-d '{
  "hash": "6dc7d304dec4434f4c4202ec42817f83",
  "tracker_id": "10033823",
  "from": "2023-12-12T09:00:00Z",
  "to": "2023-12-12T09:25:00Z",
  "columns": ["lat","lng","discrete_inputs.1","inputs.board_voltage"]
}'

The output for a raw data request will always contain a msg_time column that contains timestamps according to the user account time zone. If you need to obtain msg_time in any other time zone, please refer to the Time zone section below.

Regular Date and Time¶

Another valid option to specify date and time is the usual YYYY-MM-DD HH:mm:ss format. Since this is not the default format, you need to specify the parameter iso_datetime=false in the API request.

API request example:

curl -X 'POST' \
'https://api.eu.navixy.com/dwh/v1/tracker/raw_data/read' \
-H 'accept: text/csv' \
-H 'Content-Type: application/json' \
-d '{
  "hash": "6dc7d304dec4434f4c4202ec42817f83",
  "iso_datetime": false,
  "tracker_id": "10033823",
  "from": "2023-12-12 14:00:00",
  "to": "2023-12-12 14:25:00",
  "columns": ["lat","lng","discrete_inputs.1","inputs.board_voltage"]
}'

In this case, the retrieved data will be in the time zone of the user account.

Time Zone¶

There may be situations when you need to obtain data in a specific time zone different from the user account. This can be useful when the customer's time zone differs from yours due to geographical reasons.

In this case, you need to supplement your request with the time_zone parameter and specify the required zone ID. You can request all the possible zone IDs using the timezone/list request from the Backend API.

API request example:

curl -X 'POST' \
'https://api.eu.navixy.com/dwh/v1/tracker/raw_data/read' \
-H 'accept: text/csv' \
-H 'Content-Type: application/json' \
-d '{
  "hash": "6dc7d304dec4434f4c4202ec42817f83",
  "iso_datetime": false,
  "time_zone": "Europe/London",
  "tracker_id": "10033823",
  "from": "2023-12-12 14:00:00",
  "to": "2023-12-12 14:25:00",
  "columns": ["lat","lng","discrete_inputs.1","inputs.board_voltage"]
}'

Time Period¶

When requesting raw data, you have an option of specifying the request period in two ways: by specifying the date and time "from" and "to" or by specifying an interval. Both methods are equally valid, but you should use only one of your choice.

From ... To¶

A common way to indicate the period of data request is to specify two timestamps of start and end. This is done using the from and to parameters. The values are specified either according to ISO 8601 or in a regular YYYY-MM-DD HH:mm:ss form - as described above.

Examples:

"from": "2023-11-30T17:00:00-06:00",
"to": "2023-11-30T18:00:00-06:00",

or

"from": "2023-11-30 17:00:00",
"to": "2023-11-30 18:00:00",

Interval¶

An alternative method of indicating the request period is an interval. Here you specify the start or end date and time of the period appended by the duration of the period.

The interval can be specified in different forms:

• Starting from a specific date and time.
• Ending with a specific date and time.
• Indicated by start and end timestamps, without a period.

Possible interval parameter formats:

[start date and time]/P[dd]T[hh]H[mm]M[ss]S

or

P[dd]T[hh]H[mm]M[ss]S/[end date and time]

or

[start date and time]/[end date and time]

The date and time can be specified either according to ISO 8601 or in a regular form.

PT in interval value stands for “Period and Time” and indicates the period after the specified timestamp. For example, PT1H30M15S means 1 hour 30 minutes 15 seconds.

If you need to request data for several days, you can specify the number of days between P and T. For example, P2DT3H45M10S means 2 days 3 hours 45 minutes 10 seconds.

Examples:

• "interval": "2023-11-30T17:00:00-0600/PT1H30M10S" - data will be requested from 17:00:00 to 18:30:10, November 30 (UTC-6).
• "interval": "2023-11-30 17:00:00/P2DT2H45M10S" - data will be requested from November 30, 17:00:00 to December 2, 19:45:10 (according to user account time zone).
• "interval": "P2DT2H45M10S/2023-11-30 17:00:00" - data will be requested from November 28, 14:14:50 to November 30, 17:00:00 (according to user account time zone).