Topolert

What it does

Topolert is a low-cost, standalone early warning device that helps residents detect shallow landslides—localized disasters often missed by large-scale systems. It alerts nearby users in real time through lights and sound, enabling fast, informed action.

Your inspiration

Growing up in the mountainous region of Southwest China, I witnessed how landslides—often sudden and silent—reshape lives. I began to question why, despite advanced technology, people still lose homes and lives. I realized that most early warning systems are designed for large-scale disasters and often fail to detect shallow landslides—fast, localized events that cause the most damage. This project began with a single question: how can we create a more accessible, ground-level solution for those most at risk?

How it works

Topolert is a standalone device designed for slopes at risk of shallow landslides. It uses a low-cost soil moisture sensor and a custom algorithm to monitor real-time changes in the ground. When rainfall causes an abnormal spike in moisture—a key trigger of shallow landslides—the device immediately activates alerts through light, sound, and visual indicators. Topolert not only indicates the risk level, but also suggests concrete actions users can take—helping them respond early and decisively. Powered by solar energy and batteries, and running on an ESP32 XIAO microcontroller, Topolert operates independently of cloud infrastructure or internet access. This makes it ideal for remote, off-grid communities. Its interface is intuitive and requires no expert knowledge.

Design process

The design process began by identifying a critical gap: shallow landslides—fast, localized, and destructive—are often overlooked by current early warning systems, which focus mainly on large-scale events. These systems rely on complex infrastructure and expert interpretation, but they struggle to respond effectively to the speed and subtlety of shallow landslides. I set out to create a decentralized solution. Early tests involved custom-built soil boxes, where I observed slope behavior under varying moisture levels. I used off-the-shelf sensors and developed a threshold-based algorithm to detect abnormal spikes. Multiple sensing depths (15–50 cm) and slope angles were tested to improve sensitivity. Through 5+ rounds of prototyping, I evaluated microcontrollers, optimized the power system using solar+battery combos, and refined feedback logic using lights, buzzers, and visual color coding. I also explored moisture diffusion materials and capillary effects in soil to improve response time. Form studies followed: the device needed to be legible, weather-resistant, and easy to install on slopes. I used CAD and rapid 3D printing to iterate enclosure designs. 8+ user interviews shaped the feedback system, emphasizing clarity, intuitiveness, and actionable guidance.

How it is different

Topolert differs from existing landslide warning systems in both its focus and system design. While most systems monitor deep, large-scale events using centralized infrastructure, expert interpretation, and high-cost sensors, Topolert is tailored to shallow landslides—fast, localized, and often more destructive to individual lives. It is designed for individual use rather than institutional deployment. The device is low-cost, solar-powered, and fully independent of cloud infrastructure or mobile networks, making it ideal for off-grid areas. Unlike complex dashboards or delayed remote alerts, Topolert provides real-time, perceptible warnings Its innovation lies in integrating intuitive communication, distributed sensing, and material-based sensor optimization into a single plug-and-play system. By turning complex detection into direct local action, Topolert brings early warning capability to places and people traditional systems often overlook.

Future plans

The next step is real-world deployment. I plan to pilot Topolert in landslide-prone villages across Southwest China to test performance across terrain, weather, and community settings. This includes evaluating durability, accuracy, and usability. I’ll continue refining the hardware—improving weatherproofing, soil anchoring, power efficiency, and signal visibility. In parallel, I’ll develop an open-source deployment guide and seek partnerships with NGOs, environmental agencies, and schools to expand access. My long-term goal is to build a scalable, low-cost production model that brings early warning to high-risk, low-resource communities.

Awards