# subterraneansystems (@subterraneansystems) on tiktok

- id: koinon:creator:tiktok_subterraneansystems
- url: https://koinonlink.com/kol/tiktok/subterraneansystems
- schema_version: 1.4

## Identity
- platform: tiktok
- handle: subterraneansystems
- platform_url: https://www.tiktok.com/@subterraneansystems
- website: https://youtube.com/9nl
- country: United States
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 17655
- following: 59
- posts_observed: 1
- verified: false
- size_tier: koc

## Engagement
- status: not_collected
- status_note: Engagement has not been collected for this creator yet. This is a gap in our collection, NOT a statement that the creator has no engagement. Follower count is known, so it is measurable.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: software
- subcategory: devtools
- category_confidence: 0.9
- category_source: derived_from_recent_content
- topics: DIY rotating LiDAR scanner builds, SLAM and point cloud mapping pipelines, Cave mapping field tests and scans, ROS2, motor control, and custom PCB integration, Robotics R&D process and debugging
- bio: Build, break, iterate. 

Drones | Robotics | Autonomy
 
Email: [contact removed]

## Audience (inferred)
- status: present
- description: DIY robotics builders and engineers working on LiDAR, SLAM, and autonomous mapping systems
- roles: dev
- seniority: practitioner
- pain_points: SLAM drift and divergence making reliable mapping difficult, Integrating rotating LiDAR with motor control and avoiding wire tangling, Point cloud registration, deskewing, and processing large datasets without commercial tools, Debugging sensor fusion (optical flow, GPS, LiDAR odometry) in real-world environments like caves
- posts_analysed: 66
- confidence: 0.9

## Commercial (inferred)
- audience_buyer_fit: 0.9
- promotion_intent: 0.8
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 47
- authenticity_basis: profile_shape_only
- credibility_score: 47
- flagged_for_review: false
- koinon_bd_grade: B — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [tiktok_subterraneansystems#9eaf084d] Early bring-up, running a badly tuned optical flow + GPS EKF and a lot of hope.. Estimate gives up mid-flight. Oops. On the road to integrating LiDAR odometry and removing the GPS, plus building a cage around it for confined-space flight. (https://www.tiktok.com/@subterraneansystems)
- [tiktok_subterraneansystems#a9c65085] original sound - subterraneansystems
- [tiktok_subterraneansystems#89b62444] Check out subterraneansystems’s video! #TikTok >
- [tiktok_subterraneansystems#6b7e645e] Search:
- [tiktok_subterraneansystems#8ebd5bc2] GPS Tracker For Car
- [tiktok_subterraneansystems#84d0fe83] GPS dies the moment you go underground. The goal is a drone that maps caves without it, but I’m not there yet... this is the foundation. Right now, GPS is still on the aircraft for redundancy. The plan is deliberate: get the airframe tuned and flying clean, then start comparing t

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.9, freshness_days=67, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.9, freshness_days=67, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.9, freshness_days=67, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=67, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=67, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=67, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.25, freshness_days=67, method=Profile-shape heuristic from a single snapshot (follower count, following ratio, account age, posting volume, verification), reduced for engagement red flags where post engagement was collected. Where only a follower count is available the score saturates at 58. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=67, method=llm_partner_fit_classifier + fit_score >= 0.6 AND authenticity >= 60 => A; fit_score >= 0.4 AND authenticity >= 45 => B; else C. authenticity < 30 or a promotional-pattern flag => quarantine. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=67, method=platform_profile

## Freshness
- profile_checked_days_ago: 67
- content_analysed_days_ago: 67
- audience_updated_days_ago: 67

## AI retrieval
- indexing_requests: 12
- user_triggered_requests: 0
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=tiktok_subterraneansystems
- Request removal: https://koinonlink.com/claim?k=tiktok_subterraneansystems
- Terms: https://koinonlink.com/for-ai