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Jam

Enhancing fuel efficiency and reducing vehicle maintenance and downtime costs, using real-time data from vehicle sensors (IoT) and a machine learning algorithm for big data analysis.

Total Cost €

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EC-Contrib. €

0

Partnership

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 Jam project word cloud

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

total    starting    poland    optimizing    iot    uk    businesses    interfaces    markets    jam    emissions    advantages    reducing    barrier    maintenance    light    operators    hours    eco    troubleshooting    designed    time    fleet    operation    solutions    thousands    put    global    solution    regulations    protocols    italy    learning    trucks    vor    details    constitute    road    compliance    subscribers    efficiency    mining    industry    machine    32    duty    off    scheduled    differences    prevention    ecu    money    agnostic    france    data    companies    business    environmental    vehicle    amount    interpretation    fleets    hundreds    passenger    historical    represented    germany    repairs    biggest    billion    medium    labour    efficient    euros    innovative    software    critical    constant    day    predicting    driving    parts    sullivan    fuel    2019    surpassed    algorithm    dollar    save    compares    hardware    agriculture    physical    2011    vehicles    spain    117    ghg    million    sensor    frost    industrial    competitive    heavy    market    single    events    portugal    obd    operate    brings    2020   

Project "Jam" data sheet

The following table provides information about the project.

Coordinator
STRA, SA 

Organization address
address: INSTITUTO PEDRO NUNES, RUA PEDRO NUNES QUINTA DA NORA, ED.D
city: COIMBRA
postcode: 3030 199
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 Portugal [PT]
 Project website http://stratio.pt/jam/
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3.4. (SOCIETAL CHALLENGES - Smart, Green And Integrated Transport)
2. H2020-EU.2.3.1. (Mainstreaming SME support, especially through a dedicated instrument)
 Code Call H2020-SMEINST-1-2015
 Funding Scheme SME-1
 Starting year 2016
 Duration (year-month-day) from 2016-02-01   to  2016-05-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    STRA, SA PT (COIMBRA) coordinator 50˙000.00

Map

 Project objective

Jam is an IoT solution (hardware & software), aiming to improve the efficiency of businesses operating medium/heavy-duty vehicle (e.g. passenger and distribution fleets) and industrial fleets (e.g. mining trucks and agriculture vehicles), targeting key needs: - Fuel efficiency: fuel represented, in 2011, 32% of the total cost of fleet operation - Compliance with environmental regulations and reduction of GHG emissions - Vehicle off-road (VOR) time and maintenance costs: Many operators put the cost of having a single VOR as being in the hundreds, if not thousands, euros/day

According to Frost & Sullivan, the OBD market is expected to reach 117.8 million subscribers in 2019 and to become a billion-dollar industry by 2020. Although there are already solutions on the market for ECU interpretation on light-duty vehicles, the amount of new protocols, physical interfaces and differences in details in the way industrial vehicles operate constitute a barrier, not yet surpassed. Business and industrial fleets need an agnostic solution that allows optimizing the fleet management by reducing the maintenance costs and VOR time. Jam brings an innovative approach and focus on prevention and constant analysis of real-time vehicle data through a machine-learning algorithm allowing companies to save money on fuel costs, vehicle parts and hours of labour due to a more efficient management of fleet resources.

Competitive advantages: - Designed for medium/heavy-duty and industrial vehicles - Agnostic system - Machine-learning algorithm that compares the ECU sensor data with historical data, predicting critical events - New eco-driving approach - Troubleshooting and scheduled repairs approach focused on prevention and constant analysis of real-time vehicle data The solution will be implemented at a global scale, starting in European markets: Portugal for early market uptake and testing; and then the biggest EU markets (Germany, UK, France, Poland, Italy and Spain).

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

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