Animal identification and data management using RFID technology

Anu, V. Maria; Deepika, Malini; Gladance, L.Mary

doi:10.1109/iciict.2015.7396069

Cited by 17 publications

(11 citation statements)

References 5 publications

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“…Studies related to the development of livestock information systems are still relatively new. Some literature develops systems ranging from PC-based applications using simple databases such as Microsoft Access [5], [10], clientserver based [17], web-based [12], [13], [18], [19], based on mobile applications [20], based on cloud computing [4], [6]. All papers that focus on aspects of prototype development have no indication of how far this system is used in real farms.…”

Section: Livestock Management Systems (Limas)mentioning

confidence: 99%

Socio-technical Approach to Agricultural Information Systems Development

Hariyanto¹,

Anwar²

2019

Proceedings of the 1st International Conference on Advanced Multidisciplinary Research (ICAMR 2018)

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Agricultural information interacts with and influences agricultural productivity in informing decisions regarding land, labour, livestock, capital and management. Relevant, reliable and useful information and knowledge can arguably improve agricultural productivity. The creation of information systems to disseminate information to farmers has become a necessity. Farmers can make better decisions in order to take advantage of market opportunities and manage continuous changes in their production systems. In Indonesia, several information systems to support agricultural activities has been initiated by government bodies and private entities, from providing agricultural extension services to supporting access to market. Most existing publications looking at the initiatives are based on prototype testing and with technology based approach, little attention was given social aspect or economic impact. Socio-technical design is an approach that give equal weight to technical and social issues when designing new system. Socio-technical approach has been used extensively in organizational settings and particularly in the field health information systems. This paper will look at the approach in the context of agricultural information systems design and implementation in Indonesia focusing on the livestock management systems.

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Section: Livestock Management Systems (Limas)mentioning

confidence: 99%

Socio-technical Approach to Agricultural Information Systems Development

Hariyanto¹,

Anwar²

2019

Proceedings of the 1st International Conference on Advanced Multidisciplinary Research (ICAMR 2018)

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“…A CNN with character embeddings However, qualitative features can be evaluated by using learned weight vectors and learned character embeddings. In [21] propose an empirical explanation of ConvNets for text classification. The concepts proposed are:…”

Section: Related Workmentioning

confidence: 99%

Deep Learning Based Truth Discovery Algorithm for Research the Genuineness of Given Text Corpus

2019

ijrte

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Lot of research has gone into Natural language processing and the state of the art algorithms in deep learning that unambiguously helps in converting an English text into a data structure without loss of meaning. Also with the advent of neural networks for learning word representations as vectors has helped a lot in revolutionizing the automatic feature extraction from text data corpus. A combination of word embedding and the use of a deep learning algorithm like a convolution neural network helped in better accuracy for text classification. In this era of Internet of things and the voluminous amounts of data that is overwhelming the users determining the veracity of the data is a very challenging task. There are many truth discovery algorithms in literature that help in resolving the conflicts that arise due to multiple sources of data. These algorithms help in estimating the trustworthiness of the data and reliability of the sources. In this paper, a convolution based truth discovery with multitasking is proposed to estimate the genuineness of the data for a given text corpus. The proposed algorithm has been tested on analysing the genuineness of Quora questions dataset and experimental results showed an improved accuracy and speed over other existing approaches.

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“…The second branch focuses on monitoring animal locomotives and their contact with the animal tracking environment. One application is the development of new animal animal trace system geology applications, monitoring and theft control and safety in zoos [36] for sensor technology, radio frequency identification (RFID) and global positioning system (GPS). It helps people to have a better understanding of living creatures on earth by monitoring animal movements, particularly how the animal interacts with its environment.…”

Section: Introductionmentioning

confidence: 99%

Scrutiny of Methods for Image Detection and Recognition of Different Species of Animals

2019

IJRTE

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Animal detection-based study is useful in many real-life applications. Techniques involved in animal detection are useful in observing the locomotive behavior of the engaged animal and in result it prevent harmful interruption of animals in residential areas. There are some branches of research in animal detection. Some of these branches will therefore be discussed in this journal. Humans have developed many algorithms and techniques to gain a better understanding of animal behaviour. Therefore, for early preventive measures, these technologies can also serve as a warning system for humans from encroachment of dangerous wild animals. Such tasks can be reduced to three main branches, namely animal detection, tracking and recognition. Through these papers, new approaches for study and a variety of technologies/algorithms implemented in the past are identified and appropriate ways for solving the research gaps are suggested to fill the gap.

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Animal identification and data management using RFID technology

Cited by 17 publications

References 5 publications

Socio-technical Approach to Agricultural Information Systems Development

Socio-technical Approach to Agricultural Information Systems Development

Deep Learning Based Truth Discovery Algorithm for Research the Genuineness of Given Text Corpus

Scrutiny of Methods for Image Detection and Recognition of Different Species of Animals

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