智能回收箱

随着环保意识的增长，对创新回收解决方案的需求前所未有。Phygrid 推出智能回收箱，一种革命性的方法来鼓励和激励消费者的回收努力。这些智能箱体有各种形状和尺寸，配备秤以精确称量回收内容物。

通过数字集成赋能回收

数字集成是将回收从日常任务转变为有价值体验的核心。通过将智能回收箱与 Phygrid 数字平台和忠诚度计划连接，我们为可持续行为提供即时奖励，并教育消费者了解回收的影响。

核心功能：

__忠诚度计划集成：__用户可以根据回收物的重量获得奖励。
__数字标牌教育：__实时反馈回收物的环境影响，如等效二氧化碳节省量。
__二维码奖励：__扫描二维码领取奖励并参与环保教育内容。
__灵活的应用集成：__通过应用追踪回收贡献、管理忠诚度积分和查看个人环境影响报告。

智能回收箱的商业优势

__增强客户忠诚度：__通过奖励回收建立积极的客户关系。
__促进应用互动：__通过应用集成增加用户交互。
__推动可持续发展计划：__即时奖励激励积极参与。
__展示环保领导力：__展示对可持续发展和创新的承诺。

用 Phygrid 改变回收方式

加入迈向更可持续未来的运动，Phygrid 智能回收箱让技术与环保责任结合，共创更绿色的地球。

Global operations

50+ countries

Signals per month

0.5+ Billion

Purchases per month

35+ Million

Story

Transforming retail through a connected suite of intelligent apps. From shopper engagement to operational insight, each app is built to enhance in-store experiences and deliver measurable results.

Social

See how our apps bring retail spaces to life. Follow us to explore real-world deployments, customer stories, and new ways data-driven experiences are shaping the future of stores everywhere.

Pricing

Flexible plans that scale with your store network. Choose the apps that fit your goals — from single-store pilots to global rollouts — and connect seamlessly with your edge infrastructure as your needs evolve.

Praise for Phygrid

The numbers speak for themselves. Customer engagement has been very positive since we launched.

Alex Bilbao H&M Business Development

AI driven mirror using speech and vision really helps the consumers passing through the store get familiar with their fashion.

Satya Nadella Microsoft CEO

Why Phygrid?

Cloud/Edge based
AI Enhanced
Composable
Secure & compliant
Great developer experience

One platform for everything physical in digital spaces. No one else comes close.

Feature	Phygrid	AWS Greengrass	Azure IoT Edge	Balena	NVIDIA Fleet
Feature	Phygrid	AWS Greengrass	Azure IoT Edge	Balena	NVIDIA Fleet
Multi-arch support Support for Intel, ARM, NVIDIA architectures.
GPU acceleration Hardware-accelerated computing capabilities.
ML framework support Support for machine learning frameworks.
OS & device management Operating system and device management capabilities.
Application management Application lifecycle management.
Employee / visitor UI/UX User interface for employees and visitors.
MLOps Machine learning operations and lifecycle management.
Peripheral management Management of connected peripheral devices.
MCP/LLMs environment interactions Multi-channel protocol and large language model interactions.
Analytics & dashboards Real-time analytics and dashboard capabilities.
Access management (location) Location-based access control and management.
Resilient Edge Network stack Robust edge networking capabilities.