scholarly journals Energy and Storage Optimization In Precision Livestock Farming

2021 ◽  
Author(s):  
Simón Marín Giraldo ◽  
Julian David Ramirez Lopera ◽  
Mauricio Toro ◽  
Andres Salazar Galeano
Keyword(s):  
Pattern Recognition ◽  
Compression Algorithm ◽  
Seam Carving ◽  
Livestock Farming ◽  
Compression Algorithms ◽  
Precision Livestock Farming ◽  
Image Scaling ◽  
Storage Optimization ◽  
Original Size ◽  
And Storage

This work introduces some of the most widely usedcompression algorithms, and their relevance to the field oflivestock farming, which has been historically characterizedfor requiring menial and inefficient labor, introducingenvironmental. And also for lacking the scale andautomation that cutting edge technologies can provide. Bydoing this we will explain how this opens the door tolocations untouched by technology, and the generaladvantages, and possibilities that integrating patternrecognition models bring to the table. In addition, we willexplain the ins and outs of these compression algorithms,and our reasoning behind our decision to choose analgorithm to implement in our pattern recognition model.To solve this problem, Seam Carving, Image Scaling andRun-Length encoding were used. With them we compressedthe images an average of 17.5% of their original size in atime complexity of O(L*N*M). This research shows howyou can create an efficient compression algorithm for usagein PLF.

scholarly journals Compression Algorithms to Optimize Battery Consumption in Precision Livestock Farming.

2021 ◽  
Author(s):  
Maria Isabel Arango Palacio ◽  
Isabella Montoya henao ◽  
Andres Felipe Agudelo Ortega ◽  
Mauricio Toro
Keyword(s):  
Fourier Transform ◽  
Image Compression ◽  
Huffman Coding ◽  
Food Proteins ◽  
Livestock Farming ◽  
Compression Algorithms ◽  
Precision Livestock Farming ◽  
Day By Day ◽  
Good Compression ◽  
World Supply

The 34% world supply of food proteins comes from livestock and the need to supplement it, makes that the number of animals rearing increases day by day. Nowadays, this process is not effective due to the farmers not having the correcttools and devices to minimize their energy consumption. In line, the objective of this project is to design an algorithm that helps to compress and decompress images to optimize the energy that is required for classifying and obtaining theinformation of the animals. The algorithms that we imple?mented to achieve the objective previously mentioned were the lossy image compression with Fast Fourier Transform and lossless image compression with Huffman Coding, they were the ones that gave us the best results in terms of complexity execution time, the least possible loss of information and with a good compression ratio.

scholarly journals A blueprint for developing and applying precision livestock farming tools: A key output of the EU-PLF project

2017 ◽  
Vol 7 (1) ◽  
pp. 12-17 ◽  
Author(s):  
Marcella Guarino ◽  
Tomas Norton ◽  
Dries Berckmans ◽  
Erik Vranken ◽  
Daniel Berckmans
Keyword(s):  
Livestock Farming ◽  
Precision Livestock Farming ◽  
The Eu

scholarly journals ATLAS Event Store and I/O developments in support for Production and Analysis in Run 3

2020 ◽  
Vol 245 ◽  
pp. 02031
Author(s):  
Marcin Nowak ◽  
Peter van Gemmeren ◽  
Jack Cranshaw
Keyword(s):  
Event Processing ◽  
Analysis Model ◽  
Storage Container ◽  
Compression Algorithms ◽  
Event Selection ◽  
Atlas Experiment ◽  
Processing And Storage ◽  
And Storage ◽  
Processing Framework ◽  
Entry Number

During the long LHC shutdown, ATLAS experiment is preparing several fundamental changes to its offline event processing framework and analysis model. These include moving to multi-threaded reconstruction and simulation and reducing data duplication during derivation analysis by producing a combined mini-xAOD stream. These changes will allow ATLAS to take advantage of the higher luminosity at Run 3 without overstraining processing and storage capabilities. They also require significant improvements to the underlying event store and the I/O framework to support them. These improvements include: 1) an overhaul of the Run 2 I/O framework to be thread-safe and minimize serial bottlenecks, 2) introduction of new immutable references for object navigation, which don’t rely on storage container entry number so data can be merged in-memory, 3) using filter decisions to annotate combined output stream to allow for fast event selection on input and 4) selecting optimized compression algorithms and settings to allow efficient reading of event selections.

Evonik treibt den digitalen Hühnerstall voran

agrarzeitung ◽  
2021 ◽  
Vol 76 (14) ◽  
pp. 6-6
Author(s):  
Deborah Lippmann
Keyword(s):  
Livestock Farming ◽  
Precision Livestock Farming

Der Spezialchemiekonzern aus Essen hat sich das Ziel gesetzt, mehr Tierwohl in die Ställe zu bringen. Mit Precision Livestock Farming soll dieses Ansinnen umgesetzt werden.

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