RAPID ASSESSMENT SYSTEM FOR INFRASTRUCTURE IN EMERGENCIES

"SERIE is a smart system that allows to raise truthfully information, coordinate help in a fast and efficient way (before, during and after an emergency) saving time and resources."

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Evaluator's formation

We prepare, form and recruit volunteers.

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Evaluation Application

Damage evaluation smart system.

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Visualization Platform

Real-time, integrated and visual information for decision making.

Evaluator's formation

SERIE is an online training and preparation system for volunteers and evaluators, focusing on damage recognition. It also prepares volunteers to use SERIE’s system in a real case scenario and to develop skills to work on-field after an emergency.

Serie uses an e-learning platform to prepare, train and certify evaluators and volunteers from all over the country. Depending on their skills and knowledge they are assigned to one of the following categories: pollster, evaluator or expert.

Volunteer to SERIE

Pollster

Responsible of performing on site data gathering in emergency zones. The pollster uses the mobile app to geo-reference housing, add information to the assessment instrument and take photographs of visible damage. .

Evaluator

The system prepares and certify engineering, construction and architecture bachelors to do perform damage evaluations during the first 72 hours after a catastrophe.

Expert

PrOfessional and/or expert in building damage assessment. Needs to be trained, certified by SERIE to lead an evaluator's team.

Mobile Application for damage evaluation

The pollster uses the mobile application to regsiter data about the house (Address, GPS Location), it's occupants (Family composition, social information) and finally damages and/or service problems.

SERIE assist the damage evaluation using AI tecnologies and image recognition, which adds valur to the pollster's experience and training to obtain high quality information.

The final result indicates if a building has to be evacuated (Red light), it's safe (Green light) or has to be re-evaluated on detail by an expert (Yellow Light).

Data gathering and Geocoding

Even though Chile is the most seismic country in the world, data gathering is still made on paper.

SERIE uses mobile technologies to register data, in a fast, easy and secure way. If possible, it uses free sources of information in order to make the pollster's job easier.

The app also allows to register information in offline mode, important feature in rural areas where Internet is not available or due to failures in conectivity during blackouts.

Machine Learning

Decision making process in structural damage assessment is complex, it requires an expert, it's expensive and time consuming: often non-expert evaluators make wrong decisions.

With the help of Machine Learning and photo pattern recognition technologies, usign data already gathered from similar cases, we can improve the quality of the information, in order to reduce time making decisions and avoid common mistakes.

Product

At the beginning of the evaluation, with a few questions, the system is capable to suggest if the building need to be evaluated. The system outputs three different early states.

Green: Pollster can finish the evaluation and continue with the next building.

Yellow: Pollster needs to fully complete the evaluation in order to improve the system's final decision or call for support.

Red: The pollster con finish the evaluation and the system asks an expert to chack and declare the non-habitable condition of the structure.

Platform

The platform allows to display a dashboard with different types of information and maps on real-time, which are an essential part of many organizations workflow to handle an emergency (Government, NGOs, Companies).

SERIE allows to personalize the information delivered to each one of the organizations, create alerts and filters for handling work and live check the field work done by SERIE pollsters.

Real-Time updates

Wireless mobile server allows team leaders and evaluators to upload data through a dedicated internet mobile system, especially useful when mobile providers are out of service or during blackouts.

Machine Learning

The system allows to identify faulty, wrong, delayed or incomplete evaluations and also learn from similar or recurrent target buildings and types of damage.

Personalized platform

Clients can modify certin aspects of the platform, changing questions, manage evaluators profiles and access to data in order to fill their needs.

Geocoded information

The system uses the GPS information collected from a mobile device to individualize cases, create damage heat maps and planify evaluators routes.

Suscription to SERIE

Open Platform

The most open system, with information for the general public, without individual case visualization or filters.

Standard Platform

For users and/or institutions which have a particular interest on one or many dimensions to provide the response for specific needs on a case-to-case basis. Allows diagnose and search for condensed historic data.

Personalized Platform

Allows the full access to the informations collected, check the individual evaluations and pollsters, advanced statistical data and multi-dimensional damage scales. Also allows for special and personalized evaluation systems.

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Team

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Joaquin Gonzalez
Architect (University of Chile)
CEO

Led the team from the University of Chile which evaluated 100.000 households after the 27F earthquake.

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Philippe Delteil
Computer Science Engineer (University of Chile)
CTO

Former developer of the assessment platform used after the 27F earthquake in Chile.

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Pilar Beltrán
Architect (University of Chile)

Architect.

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Camilo Prats
Architect (University of Chile)

Architect.

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Gabriel Dintrans
Computer Science Bachelor (University of Chile)

Experience with mapping and geocoding. Has worked with Chilean National Office of Emergency and it's a colaborator of the OpenStreetMap Foundation.

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Elizabeth Contreras
Master in Public Management (University of Chile)

Experience on design and execution of proyets on social innovation and volunteer management.

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Luis Goldsack
Architect (University of Chile)

Associate Professor at University of Chile, expert in pathologic analisys of buildings and damage evaluation to houses.

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Francis Pfenniger
Architect (Catholic University of Chile)

Associate Professor at University of Chile, expert in pathologic analisys of buildings and damage evaluation to houses.