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APMAV

Innovative drone-based solution for agriculture

Total Cost €

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EC-Contrib. €

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Partnership

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 APMAV project word cloud

Explore the words cloud of the APMAV project. It provides you a very rough idea of what is the project "APMAV" about.

agricultural    flight    decision    rapid    sent    uav    diseases    language    speaks    full    farmers    valuable    discrimination    give    qualities    improves    intelligent    tractors    tool    platform    frameworks    time    tractor    hemav    hyperspectral    chemical    last    performance    recommendations    phytosanitary    services    leveraging    cameras    analyze    harvest    intuitive    detection    provides    erps    automatically    organoleptic    web    secure    fruit    software    data    costumer    leader    plagues    drive    added    displays    digital    computer    acquired    drone    thanks    industry    machine    fertilization    actionable    learning    big    solution    entrance    vision    reporting    tools    mentioned    agriculture    anomalies    deep    algorithms    thermal    era    farming    crop    cloud    planning    consists    irrigation    hydric    reports    stack    portal    multispectral    prediction    techniques    specialized    center    sensors    apmav    sme    commoditization    farmer    uavs    civil   

Project "APMAV" data sheet

The following table provides information about the project.

Coordinator
HEMAV TECHNOLOGY SL 

Organization address
address: CALLE CARLOS TRIAS BERTRAN 4 1A PLANTA
city: MADRID
postcode: 28020
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Project website https://hemav.com/proyecto/apmav/
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3.2.4. (Sustainable and competitive bio-based industries and supporting the development of a European bioeconomy)
2. H2020-EU.3.2.1. (Sustainable agriculture and forestry)
3. H2020-EU.2.3.1. (Mainstreaming SME support, especially through a dedicated instrument)
4. H2020-EU.3.2.2. (Sustainable and competitive agri-food sector for a safe and healthy diet)
 Code Call H2020-SMEINST-1-2016-2017
 Funding Scheme SME-1
 Starting year 2017
 Duration (year-month-day) from 2017-03-01   to  2017-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    HEMAV TECHNOLOGY SL ES (MADRID) coordinator 50˙000.00

Map

 Project objective

HEMAV, a technology-based SME leader in civil services with UAV, is developing APMAV, the tool that will ensure the entrance of the European agriculture in the digital era and the 4.0 Industry. It consists in a full stack approach, leveraging several technology developments including deep learning frameworks, advancement in computer vision, and rapid commoditization of sensors, cameras, and UAVs to address the above-mentioned challenges. APMAV consists of an intuitive solution for agricultural management based on drone technology and an intelligent cloud-based platform, that provides farmers valuable, actionable and real-time recommendations that drive down costs and improves crop performance. Data is acquired with thermal, multispectral or hyperspectral sensors by HEMAV's drone during flight and is sent automatically to the cloud-based HEMAV Data Center for processing. Specialized reports are generated by a software and algorithms developed during the last two years by HEMAV to analyze anomalies in the fields and give specific recommendations to the farmer. A secure web portal displays the reports that a costumer can access. Moreover, specific recommendations can be integrated automatically with other farming tools as tractors, irrigation systems or ERPs (Drone-to-tractor technology).

Thanks to big data and machine learning techniques, APMAV will provide value-added reporting to farmers aiming at improving their decision-making process and the exploitation management. These are: 1) Application of phytosanitary products, fertilization and irrigation; 2) Harvest planning; 3) Detection and prediction of plagues and diseases; 4) Fruit organoleptic or chemical qualities discrimination; 5) Discrimination of areas according to the fertilization potential; 6) Determination of the hydric condition. All of this will be achieved through an easy-to-use support decision tool that “speaks” the farmer’s language.

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The information about "APMAV" are provided by the European Opendata Portal: CORDIS opendata.

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