# Project Baobab – Off-grid solar AI edge nodes with micro-payout incentives

> Source: <https://github.com/wesleyzecaamino-rgb/project-baobab>
> Published: 2026-10-29 12:56:40+00:00

**Decentralized Edge AI Mesh Orchestrator with Automated Micro-Payments**

Project Baobab is a lightweight, decentralized edge-computing orchestrator designed to shard complex AI tasks across distributed, low-power edge nodes (e.g., Raspberry Pi 5, off-grid hardware) and automatically settle real-time compute rewards via micro-payments.

Traditional centralized AI infrastructure relies on massive, power-hungry data centers that draw heavily from centralized energy grids and create high operational costs.

**Project Baobab** flips this paradigm by creating a localized, peer-to-peer compute network:

- **Green AI Infrastructure:** Designed to run on low-cost edge nodes powered by localized renewable energy (solar/battery storage).
- **Automated Micro-Economies:** Nodes complete local inference tasks and receive instant micro-payouts using the PayPal REST API v2, creating a self-funding infrastructure model.
- **Distributed Parallel Processing:** Prompts and compute workloads are sharded concurrently across available network nodes, eliminating single points of failure.

- 🔀 **Task Sharding Engine:** Uses Python's`concurrent.futures` thread execution to dispatch workloads across multiple edge nodes simultaneously.
- 💳 **Automated PayPal Micro-Payouts:** Real-time OAuth 2.0 authentication and automated payment order creation (`v2/checkout/orders` ) triggered upon verified task completion.
- 🛡️ **Edge-Native Resilience:** Built to handle asynchronous network responses, low latency, and modular node expansion.
- 🔌 **Zero-Footprint Deployment:** Lightweight architecture runnable on laptops, mini-PCs, or single-board computers (Raspberry Pi 4/5).

- **Language:** Python 3.10+
- **Concurrency:**`concurrent.futures` / Threading
- **APIs & Protocols:** PayPal REST API v2 (OAuth 2.0 Client Credentials), HTTP REST, JSON payloads
- **Environment:** Cross-platform (Linux / Debian / Ubuntu / Raspberry Pi OS)

Ensure you have Python installed on your system:

```
python3 --version
```


