Zabasta, A., Kunicina, N.,  Grunde, U., Judvaitis, J., Sematovica, I. (2020) Implementation of IoT Concept for Early Diagnostic of Subacute Rumen Acidosis in Cows.  Conference: 2020 9th Mediterranean Conference on Embedded Computing (MECO), 1-4. doi: 10.1109/MECO49872.2020.9134092

Including 8th International Conference on Cyber-Physical Systems and Internet-of-Things (CPS&IoT’2020): Proceedings, Montenegro, Budva, 8-11 June, 2020. Piscataway: IEEE, 2020, pp.162-165. ISBN 978-1-7281-6949-1.


Highly productive dairy cow’ ration under intensive production conditions causes the development of subacute rumen acidosis (SARA). In this paper we discuss a reticulo-ruminal long-acting cyber-physical diagnostic system’ prototype, which applies Internet of Things (IoT) for monitoring rumen parameters of cows. The new diagnostic system architecture includes, reticulo-ruminal bolus with pH and temperature sensors, a microcontroller, a radio transmitter and a power supply module. The system includes gateways for data collection from boluses, an MQTT (Message Queuing Telemetry Transport) broker, a web server and a database. The diagnostic system’ prototype provides timely data on cow health status to the users, so they can evaluate the cow’ health status and implement further actions. Therefore, the use of diagnostic system provides opportunity to increase cow productivity, longevity and to save maintenance cost of milk farms. The results of the first stage of the research are discussed in this paper.