IoT for Development of Smart Dairy Farming

Akbar, Muhammad Osama; Khan, Muhammad Saad; Ali, Muhammad Jamshaid; Hussain, Azfar; Qaiser, Ghazia; Pasha, Maruf; Pasha, Urooj; Missen, Malik Saad; Akhtar, Nadeem

doi:10.1155/2020/4242805

Cited by 56 publications

(17 citation statements)

References 23 publications

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“…sleeping and grazing. By knowing this the farmer can make necessary adjustments towards feeding conditions to prevent wastage of food and overfeeding by utilizing IoT technologies [61].…”

Section: ) Feed Intake Monitoringmentioning

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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“…sleeping and grazing. By knowing this the farmer can make necessary adjustments towards feeding conditions to prevent wastage of food and overfeeding by utilizing IoT technologies [61].…”

Section: ) Feed Intake Monitoringmentioning

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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“…We referred to [19][20][21] to gain an overview of the use of sensors in agriculture. The research in [22] focused on different automated processes, like milking and feeding. Even though this article considered dairy farms, it is possible to apply this basic knowledge on the IoT in other farming infrastructures, leading to better production.…”

Section: Introductionmentioning

confidence: 99%

Towards Smart Agriculture Monitoring Using Fuzzy Systems

et al. 2021

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Conventional farming is labor-consuming and the need to continuously monitor crops can be a burden for farmers. By realizing the concept of smart farming based on Internet of Things (IoT) technology, farmers can use a mobile application to observe and monitor air humidity, air temperature, and soil moisture-factors that can affect plant growth. Furthermore, the use of timers to control the pumps in conventional watering systems is not always practical in real-life cases. This paper proposes a framework that enables advanced fuzzy logic to control a pump's switching time according to user-defined variables, whereby sensors are the main aspect of and contributor to the system. Our proposed idea offers great potential for excellent performance as an interface between the sensors as the input and the IoT as the output medium. A comparison is made between the proposed system and manual handling. The results prove that the water consumption and watering time has been reduced significantly.

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“…IoT technologies have become an attractive research tool since it allows monitoring routine activities with animals, without restrictive handling, immobilization, or altering natural behavior. (Akbar et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Influence of climatic conditions on tympanic temperature and milk production in grazing cows

Vélez-Terranova

Molina

Sánchez

et al. 2021

JABB

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Vasconcelos et al 2020). Animal's body temperature is traditionally estimated through rectal and vaginal measurements; however, alternative methods like tympanic temperatures (TT) also constitute a reliable measure since some studies reported no statistical difference with rectal temperatures (Sellier et al 2014;Shu et al 2021) and high correlation with vaginal temperature (r = 0.77; Bergen and Kennedy, 2000). The differences associated with the anatomical sampling point and its response time were also validated in other studies (Scharf et al 2011;Sellier et al 2014;Godyń et al 2019). TT is an attractive alternative measure Abstract The present study aimed to analyze large volumes of tympanic temperature (TT) data to identify its use as a physiological indicator of climatic conditions and its relationship with milk production in grazing cows under tropical lowland conditions. Three dairy farms and 21 multiparous early lactation cows were included in the study. Seven animals were equipped with tympanic temperature wireless sensors within each farm, and permanent information was collected hourly for 22 days on average. Ambient temperature (AT), relative humidity (RH), wind speed (WS), precipitation (PP), and THI information were obtained from meteorological stations located close to each farm. Statistical analyses included Spearman correlations and random coefficient regression models (P < 0.05). TT presented moderate and significant correlations with AT (0.35 to 0.49), SR (0.25 to 0.32), THI (0.35 to 0.49), and RH (-0.35 to -0.49). Climatic variables like AT, PP, SR, and WS were the most contributing factors to TT prediction (R 2 =0.42 to 0.86). Grazing dairy cows in tropical scenarios accumulate heat during the day and dissipate it at nighttime, although higher producing animals deal with more problems to reach thermal homeostasis. Correlations between TT and daily milk production varied according to animal yield; however, higher TT values were related to the most productive cows. The effect of TT on milk production prediction was not conclusive among farms, possibly by animal management or others characteristics of the systems. TT determination through remote sensors allows a reliable diagnosis of the physiological temperature response to climatic conditions.

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IoT for Development of Smart Dairy Farming

Cited by 56 publications

References 23 publications

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

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

Towards Smart Agriculture Monitoring Using Fuzzy Systems

Influence of climatic conditions on tympanic temperature and milk production in grazing cows

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