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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.

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

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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