AiNetStudio® Manual


LEGAL NOTICE

.aidb© — The .aidb AI database file extension is the copyright © of Ouslan, Inc. since 1991. All rights reserved worldwide.
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Windows 10 & 11 Requires: Windows 10 or later (64-bit), .NET 9 Runtime, 4GB RAM, 200MB available disk space, Internet connection for updates.


Introduction

Open-Source App to Help Build Antigravity UFOs and Manned Drones

I’ve just launched something that sounds like science fiction — but it’s very real. An open-source C# .NET 9 Core 9 WinForms app, powered by ML.NET, that lets engineers connect AI Neural Networks directly to real-world testing devices. Whether you’re fascinated by Antigravity or the PAIS Effect, or just want to explore how AI can monitor engines for controlled drone flight, this platform gives you the tools to experiment, innovate, and push the edge of what’s possible.
At first glance, you’ll notice my website AiNetStudio.com highlights the fascinating subject of antigravity research. The Graviflyer launched a large online community of engineers working on antigravity inspired by videos of the Graviflyer, the real-world impact of my free software lies in manned drone technology and developing the AI Neural Networks to control manned drones.
By using this open-source platform, engineers and developers can:
🔧 Connect custom devices directly into the system
🧠 Build and train AI Neural Networks to monitor live engine parameters
✈️ Enable controlled flight through adaptive AI models
This tool is more than software—it’s a framework for innovation. Whether your interests are in aerospace, drone technology, or experimental research, you can extend and modify the code to push the boundaries of what’s possible.

Devices

Device Connectivity

AiNetStudio® bridges lab/bench hardware to AI neural nets on Windows. It ingests real-time signals, tags them, and streams them into model pipelines.

Typical Devices

  • Scales/Load Cells: RS-232, USB (HID/POS), or Bluetooth (SPP) weight output.
  • Temperature / Humidity: USB probes, Modbus RTU/TCP sensors, BLE GATT env. services.
  • Electrical Measurement: DMMs, power meters, DAQs, oscilloscopes via SCPI/USBTMC or TCP.
  • Actuators/Drivers: Motor/relay controllers over serial or Modbus for closed-loop tests.

How They Connect to Windows

  • USB: Virtual COM (CDC/ACM), HID, USBTMC; may require vendor driver.
  • Serial RS-232: Via USB–RS232 adapter; appears as COMx.
  • Ethernet/Wi-Fi: TCP/UDP sockets, REST, MQTT, Modbus TCP.
  • Bluetooth/BLE: Classic SPP (serial) or BLE GATT characteristics.
  • GPIB (legacy): Through USB-GPIB interfaces.

Quick Setup

  1. Install any required drivers; note the assigned COM port in Device Manager.
  2. Select Port/Protocol in AiNetStudio® (baud, parity, IP/port, or BLE device).
  3. Click Connect to start streaming; verify live readings.
  4. Optionally enable logging and AI tagging for model training.

Video Collection

Video Top


Video Bottom

AiNetStudio® allows you to search over 100 tube sites for videos on topics of interest.

Video Bottom

AiNetStudio® has a large video collection you can edit.


Patents & Papers

AiNetStudio® has a large collection of Patent & Papers you can edit and add to.


Developers


Why C# WinForms App?

AiNetStudio® had to be built as a C# .NET 9 Core 9 WinForms app with ML.NET because this combination provides the stability, performance, and flexibility necessary for a project operating at the intersection of experimental hardware and advanced machine learning. WinForms allows for fast development of a responsive and customizable desktop interface, which is critical for monitoring and controlling sensitive real-time experiments in antigravity and propulsion research. The .NET 9 Core framework ensures cross-platform reliability, modern language features, and access to the latest runtime optimizations, while maintaining compatibility with existing scientific libraries. ML.NET was essential because it brings powerful, production-ready machine learning directly into the C# environment without requiring external languages or frameworks, enabling tight integration between sensor inputs, predictive models, and adaptive control systems. This cohesive architecture ensures AiNetStudio® can process high-frequency data streams, adapt in real time, and provide researchers with the precise analytical and control capabilities needed to accelerate aerospace breakthroughs.

Why ML.NET Instead of Python

  • Single-language deployment. No Python runtime to ship, no venv/conda, no pip dependency drift. Your installer stays clean.
  • Tight C# integration. Models are strongly typed; training/inference runs inside your app domain with your DTOs and services.
  • Works fully offline. Training and prediction happen on the client with no external services—important for your accounting app.
  • Good fit for your tasks. Classification, anomaly detection, forecasting, and AutoML are built-in and sufficient for categorization, fraud/flagging, and simple time-series.
  • Production reliability. .NET’s tooling, debugging, and profiling are first-class for your team; fewer ops headaches than managing Python on end-user machines.
  • Distribution & compliance. Many enterprise desktops allow .NET apps but restrict Python; ML.NET avoids that policy friction.
  • Interop when needed. You can import/export ONNX and call out to TorchSharp if you ever need deeper models—still without Python.

Why SaaS Is Very Bad for Consumers

AINetStudio® is 100% FREE!

Our FREE Ai Software allows users to own their copy, providing greater control and alleviating risks and problems associated with the SaaS model. READ THIS: Forbes Article

SaaS (Software as a Service) is way of delivering software over the internet where users are forced to pay a subscription fee to access the software, instead of buying and owning the software. The software runs on the provider's servers and is accessed through a web browser.

In our opinion, SaaS presents serious drawbacks for consumers and is downright despicable:

  • Recurring Costs: SaaS models often involve ongoing subscription fees which means that consumers NEVER STOP PAYING for the use of the software. We say to hell with compnies using the SaaS model.
  • Data Privacy Concerns: Storing data on external servers in the cloud managed by third-party providers can raise issues regarding data security and privacy, especially if the provider experiences breaches or mishandles data. NEVER PUT YOUR DATA ON THE CLOUD !!!
  • Dependence on Internet Connectivity: Accessing SaaS applications requires a stable internet connection. Service disruptions or limited connectivity can hinder access to essential tools and data.
  • Limited Control and Customization: Consumers may have restricted ability to modify or customize SaaS applications to fit their specific needs, as they do not own the software.
  • Vendor Lock-In: Migrating from one SaaS provider to another can be challenging due to data portability issues and compatibility concerns, potentially limiting consumer choices.