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    Iot Based Livestock Precision Feeding System Using Machine Learning
    (Institute of Electrical and Electronics Engineers Inc., 2022) Sokullu R.; Tanriverdi B.Y.; Goleva R.
    The livestock sector is one of the most important sectors in modern farming, ensuring at least 33% of the protein consumed by a person with average dietary requirements. In traditional farming sheep, goats, cows and other livestock are generally bred by inserting average amounts of food supplies into predefined containers. Main goal is maximizing milk and/or meat gains. In recent years a new concept has emerged in the realm of smart farming - Precision Livestock Farming - which aims not only increasing production and efficiency in the livestock sector, but also reducing costs and ensuring adequate feeding amounts for each separate animal. This paper describes a system using two newly emerging technologies, namely IoT and machine learning. The proposed system records the biological clocks of animals according to their daily eating patterns and then based on the recorded data estimates the feeding amount and feeding times and ensures they are according supplied with food. © 2022 IEEE.
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    Real-Time and Near-Real-Time Services in Distributed Environment for IoT – Edge – Cloud Computing Implementation in Agriculture and Well-Being
    (Springer Science and Business Media Deutschland GmbH, 2022) Goleva R.; Sokullu R.; Kadrev V.; Savov A.; Mihaylov S.; Garcia N.
    Well-being and agriculture works of people living not only in villages but also in towns nowadays, the healthy living environment at home, in the park, in the sports center, at work, local and remote monitoring of different parameters of the body, house, garden, the greenhouse is a matter of increased interest from families. Regardless of the size of the family, garden, villas, and fields, there is a need for support of integrated smart services in real-time and near-real-time forming an adaptable family software-defined Personal Enhanced Living Environment 4.0 network configurable on the top of the existing public and private infrastructure. The scale of the network, the variety of Internet of Things parts, and the distributed edge and cloud computing services that are fragmented nowadays need to be integrated. The raw data created, data storage and data processing require a common edge-to-dew-to-fog-to-cloud approach and clear correlation to the related sectors such as water, land, house, factory, environment, parks, and infrastructure management. In this paper, an integrated approach toward services for different types of users based on the previously defined scenarios is presented. The services are software-defined and use existing infrastructure orchestrated resources that are unified, and allocated appropriately to support the functional and non-functional requirements. Private and public parts of the data, data flows, data space, and capacity for processing are considered. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.