Asynchronous Machine Detection

    You can take any desired action on detecting a machine during a call. This can be done using the following steps.
    a. Set machine_detection_url parameter while firing outbound call API.
    b. Plivo will detect machine in the background and invoke the machine_detection_url with the a set of parameters which can be used to take desired action.

    The request parameters to the machine_detection_url are:

    List of parameters sent to machine_detection_url

    From string

    The from number used to initiate the call

    Machine boolean

    This will be set to ‘true’ if machine is detected in the call

    To string

    The destination that is called during the call

    RequestUUID string

    An identifier that can uniquely identify a call

    ALegRequestUUID string

    Identifies the first leg of the call in case there are multiple legs

    CallUUID string

    The identifier used to identify the call

    IfMachine string

    This parameter can be either ‘continue’ or ‘hangup’ depending on the ‘machine_detection’ parameter set while initiating the call

    Direction string

    The direction of the call. This will be ‘outbound’ since we currently support Machine detection only on outbound calls

    ALegUUID string

    An unique identifier for the A Leg of the call

    Event string

    The event which triggered this notification. This parameter will have the value ‘MachineDetection’

    CallStatus string

    The status of the call. This will be ‘in-progress’

    Returns

    If successful this endpoint returns an unique identifier that can be used to identify the call

    Response

    HTTP Status Code: 200

    Response for a Successful call

    {
      "message": "call fired",
      "request_uuid": "9834029e-58b6-11e1-b8b7-a5bd0e4e126f",
      "api_id": "97ceeb52-58b6-11e1-86da-77300b68f8bb"
    }
    

    Response for a Queued call

    {
      "message": "call queued",
      "request_uuid": "9834029e-58b6-11e1-b8b7-a5bd0e4e126f",
      "api_id": "97ceeb52-58b6-11e1-86da-77300b68f8bb"
    }