Solution Overview
Connect devices to collect water, electricity, and HVAC consumption data. Visual analysis and intelligent scheduling help buildings save energy and reduce carbon emissions.
Low Retrofitting Costs
Low Retrofitting Costs
  • Low-power sensors for wiring-free installation
  • Protocol compatible, no need to replace terminal devices
  • Long-range transmission for minimal indoor wiring
Private & Secure AI Computing
Private & Secure AI Computing
  • Low-latency local computing power
  • Runs on LAN, keeping core data private
  • One-time investment for long-term benefits
Easy to Use & Maintain
Easy to Use & Maintain
  • Manage all devices from a single platform
  • AI-assisted, conversational operations
  • Comprehensive data interfaces for integration with multiple platforms
Scenarios & Products
Low-Cost Retrofit

Pain Points & Challenges

HVAC, lighting, and meters all speak different protocols — data sits in silos and unified control never gets off the ground.


Seeed's Solution

Add one gateway that translates every building protocol into a common language — people watch it on a panel, the AI assistant calls it directly, and nothing in the original system is touched.

  • One gateway takes in all mainstream industrial protocols
  • One interface: people watch, AI acts
  • Learns your building over time — the AI assistant keeps tuning
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Flexible Networking

Pain Points & Challenges

Wired metering in a big building is expensive to install and hard to change — every unreachable corner becomes a blind spot.


Seeed's Solution

Using LoRaWAN, Wi-Fi, Ethernet, and 4G, we enable remote data collection across complex building structures without wiring, boosting deployment efficiency.

  • Flexible multi-device networking
  • Long-range communication technology
  • Automatic network device discovery
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Local AI Analysis

Pain Points & Challenges

Everything goes to the cloud: high latency, monthly bills, and sensitive data leaving the building — anomaly response is always a beat behind.


Seeed's Solution

Our edge AI devices perform local analytics, improving response time and data privacy while reducing cloud dependency. It enables 'local data for local use.'

  • Local multi-channel AI video analysis
  • Local LLM data integration
  • LLM-based device management
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FAQ

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