Opendata, web and dolomites


Automated detection of damage to buildings

Total Cost €


EC-Contrib. €






 ADDABU project word cloud

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

area    follow    style    introduction    issue    off    describe    report    joined    idea    fast    identity    proof    business    occurring    reduce    graphical    image    damage    storm    companies    market    upload    damages    repair    varcity    eth    deal    forces    clients    casalva    swiss    mitigations    company    hail    select    spin    improves    peak    negligible    technologies    insurers    drafting    thousands    stretch    facade    people    additional    equally    automated    occurrence    events    created    spinning    structures    optimally    single    corresponding    tend    times    house    zurich    facades    remaining    computer    extreme    guaranteeing    vision    photos    submitted    half    lab    water    parse    delayed    corporate    weather    customer    expert    sales    satisfaction    risk    20    building    erc    automatically    consideration    visiting    cutting    insurance    leaking    buildings    analyze    grounded    recognize    damaged    prevents    refined    textures   

Project "ADDABU" data sheet

The following table provides information about the project.


Organization address
address: Raemistrasse 101
postcode: 8092

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 Switzerland [CH]
 Total cost 143˙750 €
 EC max contribution 143˙750 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2017-PoC
 Funding Scheme ERC-POC
 Starting year 2017
 Duration (year-month-day) from 2017-09-01   to  2018-08-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

Hail and storm damages represent the most often occurring cases for building insurance companies. Currently, the damage is estimated by an insurance expert, visiting the damaged building and drafting a report. Researchers at the Computer Vision Lab at ETH Zurich joined forces with business and sales people, spinning out the company Casalva, to strongly reduce such costs via automated image analysis. The idea is that the insurers’ clients upload photos of the damages, which will then be analyzed automatically by a computer. This involves computer vision technologies – grounded in the ERC project VarCity – to recognize the damaged building structures and to analyze the corresponding textures as to assess the extent of the damage and the estimated costs for its repair. Cutting costs is not the only consideration, as the fast assessment of damages improves customer satisfaction and prevents the occurrence of additional damages because of a delayed repair (like water leaking before repair). Such follow-on damages are estimated to be 20% of overall costs on average and are therefore far from negligible. Guaranteeing a short term response currently is a major issue, as a single storm may affect thousands of buildings. Processing times tend to stretch out due to the peak in cases following such extreme weather events. Over half of hail storm damage cases concern facade structures. The VarCity project produced methods to automatically parse facades into such structures, and to select the best way to describe their textures. These will be refined to optimally deal with the application area. The remaining technical developments and risk mitigations will be funded through other means (a Swiss project that has already been submitted), while this Proof-of-Concept project will focus on equally important aspects like market analysis, development of a corporate identity and graphical house style for the Casalva spin-off, that has been created but should now get market introduction.

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

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