RETRACTED CHAPTER: Low-Power Distributed AI and IoT for Measuring Lamb’s Milk Ingestion and Predicting Meat Yield and Malnutrition Diseases

Alonso, Ricardo S.

doi:10.1007/978-3-030-58356-9_26

Cited by 3 publications

(1 citation statement)

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“…Additionally, in sheep dairy farms separation of lambs from mothers after birth which is raised by artificial lactation is a common practice. A lowpower distributed AI device has been built to measure the ingestion of lamb's milk as well as future meat prediction and malnutrition [103]. The device consists of CLEC that identifies each lamb and measures the quantity of milk and offers farmers and researchers a prediction.…”

Section: ) Artificial Intelligencementioning

confidence: 99%

A Survey on the Role of IoT in Agriculture for the Implementation of Smart Livestock Environment

et al. 2022

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The Internet of Things (IoT) is an emerging paradigm that is transforming real-world things (objects) into smarter devices. IoT is applicable to a variety of application domains including healthcare, smart grid, and agriculture. This domain has started revolutionizing the agriculture industry by providing smart solutions for precision farming, greenhouse management, and livestock monitoring. This article aims to present a comprehensive survey on the role of IoT in the Livestock field by categorizing and synthesizing existing research work in this area. To this end, a detailed discussion has been provided on IoT network infrastructure, topologies and platforms employed for livestock management. In addition, a list of communication protocols and connections of IoT-based livestock systems with relevant technologies have also been explored. Furthermore, numerous IoT-based livestock monitoring, controlling, and tracking applications have been discussed. Apart from this, it also analyses distinct security issues in IoT-based livestock field and developed a collaborative security model to detect and minimize the security risk. Lastly, pertinent open research challenges in the domain of IoT-based livestock management have been presented with future research directions.

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Section: ) Artificial Intelligencementioning

confidence: 99%