HTTP JSON Sensor Data

Preface

• all Sensor data is available in a generic JSON Object, presented by status.json
• there are two relevant sub-objects: sensor_values and sensor_descr
• sensor_descr can tell
  • what sensor types are actually relevant
  • what is the sensor type specific field description
  • how many sensors of each type are actually present
  • what are the names of each of those sensors
• sensor_values carries all measured sensor values, matching the description explained above, in the same order
• it's common practice to get sensor_descr+sensor_values once, and poll sensor_values only subsequently with much less payload

This empowers you to write small code supporting all products and all sensors in one single future-proof approach, without the need for sensor specific knowledge.

So your software is already prepared for new gude-devices, and prepared for new sensor Add-Ons.

To give an example, this documentation will highly depend on check_gude.py, our HTTP sensor data swiss-knife tool.

Getting Data

• HTTP-Get status.json?components=8470528
  • for more info about status.json components flags, refer to EPC HTTP Interface
  • 8470528 sums up sensor_values (16384 aka 0x10000) plus sensor_descr (65536 aka 0x4000), plus the ‘extended’ marker (0x800000) to get both simple sensors and (more complex) sensor groups
  • 8470528 = 0x814000 = 0x4000 + 0x10000 + 0x800000

Example Data

sensor_descr

 [
   {
     "type": 664,
     "num": 2,
     "fields": [
        {"name": "Voltage", "unit": "V", "decPrecision": 3},
        {"name": "Current", "unit": "A", "decPrecision": 1}
     ],
     "properties": [
       { "id": "L1", "name": "Meter1", "state": 1},
       { "id": "L2", "name": "Meter2", "state": 1}
     ]
   },
   {
     "type": 665,
     "num": 1,
     "fields": [
        {"name": "Temperature", "unit": "C", "decPrecision": 1},
        {"name": "Humidity",    "unit": "%", "decPrecision": 1}
     ],
     "properties": [
       { "id": "6102", "name": "Server-Rack", "state": 1}
     ]
   }
 ]

This tells you:

• there a two Sensors of Type 664, and one of type 665
• a type-664 sensor has two Fields, Voltage and Ampere
  • Voltage is measured with a decimal precision of 3, Ampere with a decimal precision of 1
• The two Type-664 sensors (L1 and L2) are named 'Meter1' and 'Meter2'
• The Type-665 Sensor is named 'Sever-Rack'

sensor_values

 [
   {
     "type": 664,
     "num": 2,
     "values": [
       [{"v": 233.19}, {"v": 3.2}],
       [{"v": 226.2},  {"v": 0.3}]
     ]
   },
   {
     "type": 665,
     "num": 1,
     "values": [
       [{"v": 27.1}, {"v": 40.3}]
     ]
   }
 ]

sensor_desc / sensor_values

bringing together this tells you:

 L1/Meter1 233.19 V (Voltage), 3.2 A (Ampere)
 L2/Meter2 226.20 V (Voltage), 0.3 A (Ampere)
 
 6102/Server-Rack: 27.1 C (Temperature), 40.3 % (Humidity)

Common Sensor Type IDs

  1  Line power meter
  9  Line power meter with residual Current
  8  Outlet power meter

  7  Digital Inputs

 20  System Data (sensor group)

 51  Temperature Sensor
 52  Temperature/Humidity Sensor
 53  Temperature/Humidity/AirPressure Sensor

101  Bank (eFuses Port-groups) Sensor (e.g. used at 8291 PDUs)
102  (DC) Power Sources

check_gude.py in action

• check_gude.py is a demo code to show how sensor_descr and sensor_values can be assembled generically to make use of all our devices / sensors
• so when new devices and sensors are coming up, check_gude.py is already prepared to deal with it
• install python along with requests to run check_gude.py
• feel free to use check_gude.py as you need it and to rewrite the given code to any language desired

Show all Sensor Data

• Here a device with hostname 8041.demo.gude.info is queried to dump all sensor data
• with check_gude.py can use --ssl / --username / --password to benefit from HTTP encryption and user authentification

show CGI-Get / JSON Data

when using --verbose check_gude.py will print out the full URL and the JSON return data:

Sensor Groups

a simple sensor has one single field description, where a sensor group is a bundle of different field descriptions

Sensor Group example

• This is a virtual sensor 'engine', each engine has a certain amount of cylinders, and a certain amount of temperature sensors
• Each vehicle can have multiple engines
• In this example, our Car has two engines, Front-engine and Rear Engine
  • Front-engine has 4 cylinders, and 1 telemetry sensor
  • Rear-engine has 2 cylinders, and no telemetry sensor

  {
    "type": 666,
    "num": 2,
    "groups": [
       {
         "name": "cylinder",
         "fields" : [
           {"name": "flux",   "unit": "milli-brown", "decPrecision": 0},
           {"name": "Power",  "unit": "watt",        "decPrecision": 1}
         ]
       },
       {
         "name": "telemetry",
         "fields" : [
           {"name": "Temperature",    "unit": "C",   "decPrecision": 1}
         ]
       }
    ]
    "properties": [
      {
        "id": "E1",
        "name": "Front Engine",
        "groups": [
          [
            {id: "C1", name: "Cylinder1"},
            {id: "C2", name: "Cylinder2"},
            {id: "C3", name: "Cylinder3"},
            {id: "C4", name: "Cylinder4"}
          ],
          [
            {id: "T1", name: "Temperature1"}
          ]
        ]
      },
      {
        "id": "E2",
        "name": "Rear Engine",
        "groups": [
          [
            {id: "C1", name: "Cylinder1"},
            {id: "C2", name: "Cylinder2"}
          ],
          [
          ]
        ]
      }
    ]
  }