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.

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

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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