LiveCare: An IoT-Based Healthcare Framework for Livestock in Smart Agriculture

Chatterjee, Pinaki Sankar; Ray, Niranjan Kumar; Mohanty, Saraju P.

doi:10.1109/tce.2021.3128236

Cited by 42 publications

(9 citation statements)

References 23 publications

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“…Table 3 shows that the proposed Prediction-DLCNN model accurately estimated the nutrient values as compared to state-of-art approaches like EFIS [15], SVM [16], Mic-ConvNet [18], and RCNN [23]. These conventional methods considered the reference data during perfect atmospheric conditions, so they failed to result in the best prediction for all environmental situations.…”

Section: Nuonet (Nutrient Use and Outcome Network) This Dataset Is Co...mentioning

confidence: 99%

“…However, this method is not useful for diagnosis of hand full of plants and trees diseases detection. In addition, AI and IoT enabled smart agriculture technologies' [23] system is developed with decision tree classification. The data from the hardware is processed by AI, which contains valuable data for prediction of the all the parameters of crop.…”

Section: Literature Reviewmentioning

confidence: 99%

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Design and Implementation of Smart Hydroponics Farming Using IoT‐Based AI Controller with Mobile Application System

Raju¹,

Dappuri²,

Varma

et al. 2022

Journal of Nanomaterials

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Hydroponics is the soil less agriculture farming, which consumes less water and other resources as compared to the traditional soil-based agriculture systems. However, monitoring of hydroponics farming is a challenging task due to the simultaneous supervising of numerous parameters, nutrition suggestion, and plant diagnosis system. But the recent technological developments are quite useful to solve these problems by adopting the artificial intelligence-based controlling algorithms in agriculture sector. Therefore, this article focuses on implementation of mobile application integrated artificial intelligence based smart hydroponics expert system, hereafter referred as AI-SHES with Internet of Things (IoT) environment. The proposed AI-SHES with IoT consists of three phases, where the first phase implements hardware environment equipped with real-time sensors such as NPK soil, sunlight, turbidity, pH, temperature, water level, and camera module which are controlled by Raspberry Pi processor. The second phase implements deep learning convolutional neural network (DLCNN) model for best nutrient level prediction and plant disease detection and classification. In third phase, farmers can monitor the sensor data and plant leaf disease status using an Android-based mobile application, which is connected over IoT environment. In this manner, the farmer can continuously track the status of his field using the mobile app. In addition, the proposed AI-SHES also develops the automated mode, which makes the complete environment in automatic control manner and takes the necessary actions in hydroponics field to increase the productivity. The obtained simulation results on disease detection and classification using proposed AI-SHES with IoT disclose superior performance in terms of accuracy, F-measure with 99.29%, and 99.23%, respectively.

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Section: Nuonet (Nutrient Use and Outcome Network) This Dataset Is Co...mentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Design and Implementation of Smart Hydroponics Farming Using IoT‐Based AI Controller with Mobile Application System

Raju¹,

Dappuri²,

Varma

et al. 2022

Journal of Nanomaterials

View full text Add to dashboard Cite

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“…The IoT has become a part of smart poultry farms. Chatterjee et al have proposed an IoT-based framework to monitor the cows’ health on a livestock farm. IoT devices can collect data from the poultry farm with the help of environment monitoring sensors, imagers, wearable sensors, and microphones to automate the poultry farm with minimum human interference. ,, …”

Section: Role Of Emerging Technologies In Poultry Health Managementmentioning

confidence: 99%

A Literature Review on the Role of Internet of Things, Computer Vision, and Sound Analysis in a Smart Poultry Farm

Goyal,

Yadav,

Mukherjee

2024

ACS Agric. Sci. Technol.

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The rapid growth of human population and frequent changes in environmental conditions pose challenges in providing nutrient-rich food to the current population. The demand for poultry products is increasing exponentially as they are a good source of low-cost proteins. Ensuring the well-being of birds and delivering nutritious poultry products is essential for both current and future food security needs and sustainable agriculture. This article is motivated by the potential of emerging digital technologies in agriculture to provide innovative solutions to challenges faced by farmers, particularly in poultry farming. It aims to shed light on various issues encountered by farmers like diseases on poultry farms and offers valuable insights for researchers seeking to address these challenges using the advancements in digital technologies. Precision farming in poultry involves leveraging technologies such as the internet of things, artificial intelligence, and edge computing to enhance animal health management. A smart poultry farm maintains the farm environment and detects diseases at early stage in the chickens. The farm resources are utilized optimally in the smart poultry farm. This research work provides a systematic literature review of intelligent systems designed for (i) poultry birds' health and welfare management using technologies like the internet of things (IoT), artificial intelligence, cloud computing, and edge computing and (ii) early disease detection, estimation of weight, and feeding behavior of birds with the use of computer vision and vocalization analysis. This article also explores various sensors employed in the development of IoT infrastructure. It has been demonstrated in the literature that modern digital technologies automate the management operations of poultry farms. As a result, the farmer's income increases, and high-quality food products are available to people at low cost.

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“…Chatterjee et al. proposed a framework known as LiveCare, based on the IoT, for automated monitoring of the health status of cows in large‐scale dairy farms [29]. This framework tracks the behavioral changes of cows on a daily basis and introduces the Cow Disease Prediction (CDP) algorithm as a core component.…”

Section: Advancements In Ai‐driven Animal Disease Prediction Monitori...mentioning

confidence: 99%

Advancements in artificial intelligence technology for improving animal welfare: Current applications and research progress

Zhang,

Guo,

et al. 2023

Animal Research and One Health

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The integration of Artificial Intelligence (AI) in various sectors has led to significant advancements, with the animal industry being no exception. This review aims to investigate the benefits, limitations, and future prospects of AI technology in improving animal welfare. First, it examines the role of AI in understanding animal behaviors and emotions, providing deeper insights into their well‐being and sources of stress. Next, the paper explores how AI can revolutionize animal nutrition through innovative algorithms and data analytics. The health aspect emphasizes the ability of AI to identify and manage illnesses through intelligent systems. This review also highlights the application of AI in improving animal living conditions, with a focus on environmental management and automated cleaning and disinfection systems. In conclusion, the review emphasizes AI‐driven techniques for early prediction, close monitoring, and accurate diagnosis of animal diseases, ensuring healthier and more sustainable livestock management. By leveraging its advantages, addressing limitations, and exploring future directions, AI has the potential to significantly enhance animal welfare, sustainable agriculture, and veterinary practices.

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LiveCare: An IoT-Based Healthcare Framework for Livestock in Smart Agriculture

Cited by 42 publications

References 23 publications

Design and Implementation of Smart Hydroponics Farming Using IoT‐Based AI Controller with Mobile Application System

Design and Implementation of Smart Hydroponics Farming Using IoT‐Based AI Controller with Mobile Application System

A Literature Review on the Role of Internet of Things, Computer Vision, and Sound Analysis in a Smart Poultry Farm

Advancements in artificial intelligence technology for improving animal welfare: Current applications and research progress

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