SENTINELA
Security and prevention of disputes.
THE CHALLENGE
Sentinela is an innovative app developed for risk assessment of slopes throughout the state of Minas Gerais. Created specifically for Civil Defense, the app plays a crucial role in preventing and responding to adverse events in slopes throughout the Minas Gerais region.
PRECISE GEOLOCATION
With precision up to 5m, the app pinpoints risk areas, mapping vulnerable slopes with real-time GPS coordinates.
INSTANT CAPTURE
Field agents collect technical images and data in a structured way, even without a stable connection, ensuring immediate recording of local conditions.
SMART ALERTS
Automatic notifications are triggered to managers and communities in regions identified with high landslide risk.
AUTOMATED ANALYSIS
The system automatically classifies the risk level, eliminating subjectivity and standardizing technical team assessments.
IMAGINING THE SCREENS
SIMPLICITY
EFFICIENCY
ACCESSIBILITY
The Sentinela screens were designed to highlight the most important content from the very first access. Users find an intuitive interface with simplified navigation, avoiding complex menus or scattered information. The visual hierarchy was planned so that each action - assessing risk, registering occurrences or viewing maps - is just a few clicks away, keeping information always clear on screen.
Style guide
Cinza grafite
#2E2D2D
FONTE PRINCIPAL
Montserrat
Letras:
Aa Bb Cc
Números:
012345
BUILDING THE PROJECT
To carry out this redesign, we used the best tools available on the market, each with its essential role in Sentinela's success.
figma
flutter
firebase
At Sentinela, Figma was essential to create a clean and modern interface, prioritizing user experience in the security and prevention area.
THE IMPORTANCE BEHIND SENTINELA
Sentinela uses advanced models and machine learning algorithms to process images and geospatial data, detecting risk patterns that would be difficult to identify manually. This capability transforms basic measurements into high-precision scientific analyses. Each field collection contributes to an expanding database, continuously strengthening the model accuracy and the protection of Minas Gerais communities.
DIFFERENTIALS
APPLIED ARTIFICIAL INTELLIGENCE
Machine learning algorithms analyze field-collected data to automatically qualify the risk level at each recorded point.
OFFLINE ANALYSIS
Works without connection in remote areas, saving data locally and automatically syncing when signal is restored.
GEOREFERENCED MONITORING
Interactive mapping with precise markers and real-time visualization of risk regions recorded in the field.
MODULAR AND SCALABLE PLATFORM
Architecture designed for continuous growth, allowing new modules as Civil Defense expands operations.
HOW SENTINELA TRANSFORMS MEASUREMENTS INTO DECISIONS
THE RESULT
With the implemented transformations, Sentinela now presents a completely renewed identity. Each screen, each navigation flow and each detail were designed with the user in mind, offering a modern and intuitive experience for risk assessment and disaster prevention.
