By Tomisin Olujinmi

Animals communicate with signals that range from simple visual cues to complex vocalizations and gestures. Intraspecies and interspecies communication has been studied extensively in birds, dolphins, dogs, primates, and other animal species.

The field is beleaguered with challenges. Data is hard to obtain, and animal communication signals are often difficult to interpret objectively. However, with advances in machine learning and artificial intelligence, we can begin to make sense of the chirps, calls, whines, and other signals animals communicate.

According to Interspecies Internet co-founder, Neil Gershenfeld, the need for a multi-species data-logging platform first came up during the Interspecies Internet Workshop in 2024. The workshop’s proceedings showed significant effort duplication in the animal translation space, especially for data logging.

Gershenfeld proposed that the ideal data logger would be open source and collaboratively developed, modular with multimodal “sensory” interfaces, accessible to non-technical users, and integrated with a scalable data platform, to be suitable for widespread use.

Patrick Chwalek’s CollarID is a lightweight tracking device that collects environmental data (acoustics, temperature, humidity, and gas) and animal movement data (via GPS and accelerometer) at the same time. By combining both classes of data, researchers can gain valuable insights into endangered populations and answer fundamental questions about their interactions. The CollarID is still in the prototype stage and is being tested on different animals in Botswana, Chile, Kenya, and the United States.