Exploring the Differences between current S1 and S1 Pro Pre-Release Firmware: An In-depth Analysis⌗

I recently deep dived into the firmware upgrade methods of FLSUNs most recent 3D printers, for developing a jailbreak to gain remote access as superuser. While researching I noticed the anouncement of a new flagship model.

In this post I work out the differences between the firmware configurations of the Flsun S1 and its upcoming iteration, the S1 Pro. All data I analyzed stemmed from comparing two firmware versions: the S1 (V1.0.6.3) and the pre-release S1 Pro (V1.0.1.0). For those who want to take a look theirselves, I created a repository which contains all different versions I was able to find. Notably, it appears that both versions are further developments of the Flsun SpeederPad firmware, based on Debian or more precise Raspbian.

Here’s a comprehensive breakdown of the key changes and their implications.

TL;DR - For the lazy ones:⌗

  • Enhanced AI Detection: Upgraded from YOLOv5 to YOLOv8 and YOLOv10 models and added segmentation capabilities for improved object detection and print monitoring.
  • Better Thermal Management: Higher bed temperature (up to 140°C) additional to the hotter nozzel and more precise PID controls for consistent heating.
  • Improved Print Recovery: More sophisticated macros for power loss recovery, filament management, and state saving.
  • Advanced Calibration: Self-adapting pressure advance(?)
  • Klipper Configuration: Tighter integration for enhanced motion control and print customization.
  • New IoT Capabilities: Enhanced IoT capabilities and SSL support for secure, cloud-based interactions based on MQTT.
  • Updated Image Capture: Refined image capture, and process management updates. Introduction of a video feed streaming helper?
  • Fan & Cooling Adjustments: Reduced max fan power for quieter operation and optimized cooling.

Overall, the S1 Pro focuses on precision, automation, and enhanced user experience. It’s possible that FLSUN will launch a cloud platform for device management soon. At least they are working on consolidation of firmware upgrade paths for different models.

Key Differences and Implications⌗

1. Advanced AI Detection Capabilities⌗

One of the most striking changes between the two models centers around AI detection functionalities. The flsun_func/AI_detect/ directory features multiple new files and scripts not present in the current S1, including:

  • YOLO (You Only Look Once) Models: The S1 Pro introduces rknn_yolov8_demotool and rknn_yolov10_demo models, reflecting a significant upgrade from the S1’s use of yolov5.
  • Segmentation Capabilities: Files such as rknn_ppseg_demo and segzkpre.rknn suggest an enhancement in AI-based image segmentation. This means the S1 Pro can analyze print layers with finer detail and potentially detect and rectify issues more accurately.

Implications: These advancements hint at a significant leap in real-time object detection, defect identification, and monitoring. By integrating cutting-edge YOLO models and segmentation tools, the S1 Pro is poised to provide a more precise AI-driven user experience, potentially minimizing print errors and maximizing output quality. Let’s hope that FLSUN will release the upgraded models to the S1, too.

2. Workflow Refinements and Improved Feedback Mechanisms⌗

Both the aidetect.sh and before_printing_run.sh scripts showcase substantial improvements in the S1 Pro:

  • Conditional Logic Enhancements: The S1 Pro introduces new conditional checks for layer heights (z_height) and more detailed logging. This not only helps with tracking the print’s progress but also facilitates advanced troubleshooting.
  • Process Management Improvements: Transitioning from mjpg_streamer to pushStream indicates an optimization in how the S1 Pro handles image streaming during operation, potentially leading to smoother video feeds and better data management.

3. Enhanced Print Calibration and Automation⌗

The S1 Pro configuration files reveal several enhancements aimed at improving print calibration:

  • Motor Calibration Macros: More sophisticated macros for motor calibration (CLEAN_CALIBRATE_MOTOR and related scripts) in the S1 Pro indicate a stronger focus on precise motor control.
  • Self-Adapting Pressure Advance: Unlike the S1, the S1 Pro’s extruder configuration includes a self_adaption_pressure_advance parameter. This adaptive approach ensures that pressure advance settings are optimized on the fly, contributing to improved layer adhesion and reduced print defects.

Implications: These changes collectively point to a more precise and automated approach to calibration, ensuring consistent print quality and smoother operation.

4. Thermal Management and Fan Configuration Updates⌗

  • Increased Bed Temperature Range: The S1 Pro supports a maximum bed temperature of 140°C, up from the S1’s 130°C, broadening the range of materials it can print with.
  • Fan Power Adjustments: The S1 Pro limits fan power to 0.55, compared to 0.90 in the S1. This adjustment likely aims to balance cooling efficiency and noise reduction, particularly when working with temperature-sensitive materials.

Implications: These enhancements suggest that the S1 Pro offers better thermal management, potentially leading to superior print adhesion and surface finishes across various filament types.

5. New and Expanded G-code Macros⌗

The S1 Pro configuration introduces numerous G-code macros that were absent or less complex in the S1:

  • Power Loss and Print State Recovery: The S1 Pro’s macros for managing filament motion sensors, power loss, and state recovery are more sophisticated. This means users can resume interrupted prints more accurately and efficiently.
  • Automated Bed Leveling and Calibration States: The S1 Pro includes macros to save and restore leveling states, reducing manual intervention and ensuring consistent print surfaces.

Implications: These macros enhance print reliability and user convenience, particularly during long-duration prints.

Configuration Differences: Networking and System Settings⌗

Examining files like IotCfg.json and SysSetting.ini reveals changes in networking capabilities and security:

  • Enhanced IoT Configuration: The S1 Pro introduces a new UpdateHttpRequestUrl parameter and potentially more secure communication protocols, reflecting a move towards dynamic cloud interactions and firmware updates.
  • SSL Security Presence: The inclusion of an ssl file in the S1 Pro indicates a focus on data security, aligning with industry trends for IoT device protection.

Implications: These changes position the S1 Pro as a more connected and secure device, offering users improved remote management capabilities and protection against potential security risks.

A Broader Look at System and AI Upgrades⌗

The overarching theme in these firmware differences is refinement and advancement. The S1 Pro’s configuration suggests a concerted effort to improve AI-driven detection, print calibration, user feedback, and system security. While some aspects, like the 720p webcam, which is usually good enough for ML detection tasks, remain unchanged, the software enhancements can reflect a significant step forward.

Conclusion⌗

The S1 Pro firmware just represents, in it’s current WIP state, an incremental enhancement that builds upon the S1’s foundation. I can’t wait to checkout the final hardware configuration and its firmware release.

But in the end, as an owner of a S1 model I expect to see these software enhancements, in particular the AI ones, to be future firmware upgrades with no need to buy the S1 Pro.

By the way, FLSUN uses a big chunk of GPL’ed code in different components. So, remember to release this code to the public… 🤓