Remote Status and Activity Monitoring with the SM4-FS Bat Recorder

Remote Status and Activity Monitoring with the SM4-FS Bat Recorder

Overview

Wildlife Acoustics have recently added a remote logging capability to the SM4BAT-FS, designed for wind farm operators who need to know the status of their Song Meters.

This is only available on recorders with serial numbers greater than S4U06942 (manufactured from around March 2019) and running firmware 2.2.1. or later. You will also need an RS-232 data cable to connect the Song Meter to a data logger or other external system.

The new upgrade implements a serial communications interface to wind energy SCADA systems. The SM4-FS responds to serial requests with information including:

  • cumulative number of bat passes and pulses detected
  • timestamp
  • voltage
  • temperature
  • flash card capacity

Operation

The recorder is configured and operates just as it normally would when recording bats in triggered WAV mode. However, once the SD cards are full or fail, the SM4-FS will continue monitoring and counting will continue to respond to requests over RS-232 with bat activity information.

The protocol is “plug-and-play” in the sense that the SM4- FS automatically detects receiving the first request at either 38,400 or 19,200 baud while recording bats. Once detected, the SM4-FS will configure the serial port and respond to subsequent requests with information.

Recording

As in normal operation, the user can change the various parameters and settings to schedule monitoring times and to define a valid bat pulse or pass.

Individual echolocation pulses from bats and sequences of bat pulses are detected and counted using firmware algorithms based on the parameters configured by the user. Essentially this is raw data from the recorder that has not been checked by an ecologist. Some outside noise sources can cause false positives, and some bat activity will be misclassified as ‘noise’. These raw outputs should therefore be used with caution as part of a site-specific statistical model capable of correlating the data to actionable events.