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Augmented and Virtual Reality Data Visualization Tender - 64394126

The OLDS COLLEGE has issued a Tender notice for the procurement of a Augmented and Virtual Reality Data Visualization for Advancing Agronomy through Hyperlayer Data Collection and Analytics in the Canada. This Tender notice was published on 16 Mar 2022 and is scheduled to close on 28 Mar 2022, with an estimated Tender value of Refer Document. Interested bidders can access detailed Tender information, eligibility criteria, and complete bidding documents by referencing TOT Ref No. 64394126, while the tender notice number is RFP 128-2022 and Registering on the platform.

Procurement Summary

Country: Canada

Summary: Augmented and Virtual Reality Data Visualization for Advancing Agronomy through Hyperlayer Data Collection and Analytics

Deadline: 28 Mar 2022

Posting Date: 16 Mar 2022

Other Information

Notice Type: Tender

TOT Ref.No.: 64394126

Document Ref. No.: RFP 128-2022

Competition: ICB

Financier: Self Financed

Purchaser Ownership: Public

Tender Value: Refer Document

Purchaser's Detail

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Tender Details

Tender are invited for Augmented and Virtual Reality Data Visualization for Advancing Agronomy through HyperLayer Data Collection and Analytics
Project Description : The overarching goal of this project is to develop predictive algorithms based on machine learning (ML) for estimating the concentrations of plant available nutrients in soil, instant identification of yield limiting factors, calculating best achievable yield goals, and automated calculation of site-specific fertilizer prescriptions. Multiple layers of geospatial data, such as multi- and hyperspectral imagery, thermal imagery, microwave soil moisture measurements, ground penetrating radar data, high density soil tests, soil compaction, elevation data and field surface analysis, gamma-ray soil spectrometry analysis, soil electrical conductivity, and yield monitoring data, will be used to build new ML predictive algorithms, which will allow for automated analysis of various agronomic field characteristics including plant available soil nutrients and water, instant identification of yield-limiting factors, automated calculation of optimal fertilizer rates, and site-specific estimation of best achievable yield potential.
Solicitation Number : RFP 128-2022
Solicitation Type : Request For Proposal
Closing Date : 03/28/2022 02:00:00 PM Alberta Time
Agreement Type : NWPTA/TILMA
Commodity Codes : N8720: Fertilizers
U008P: End-to-End Learning Services (E...

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