{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:56232DIX64WZMVDV447G3EPSBY","short_pith_number":"pith:56232DIX","schema_version":"1.0","canonical_sha256":"efb5bd0d17f72d965475e73e6d91f20e20129f654ce3a671a1c893ef98149f4d","source":{"kind":"arxiv","id":"2504.12664","version":1},"attestation_state":"computed","paper":{"title":"Autonomous Drone for Dynamic Smoke Plume Tracking","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["physics.flu-dyn"],"primary_cat":"cs.RO","authors_text":"Jiarong Hong, Nikil Krishnakumar, Shashank Sharma, Srijan Kumar Pal","submitted_at":"2025-04-17T05:50:15Z","abstract_excerpt":"This paper presents a novel autonomous drone-based smoke plume tracking system capable of navigating and tracking plumes in highly unsteady atmospheric conditions. The system integrates advanced hardware and software and a comprehensive simulation environment to ensure robust performance in controlled and real-world settings. The quadrotor, equipped with a high-resolution imaging system and an advanced onboard computing unit, performs precise maneuvers while accurately detecting and tracking dynamic smoke plumes under fluctuating conditions. Our software implements a two-phase flight operation"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2504.12664","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-04-17T05:50:15Z","cross_cats_sorted":["physics.flu-dyn"],"title_canon_sha256":"59380e45f3449f38d991f6062a371046e1e1602db484716dc803bec7c5deb957","abstract_canon_sha256":"a3d024038d0e90a382949ed0b0f7bb196accd77704be2596553aa146e30c26b3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:50:20.360639Z","signature_b64":"LAVWM17rSGA+eq1T+29hTdhMPI4BOlyRMmwV6gtfNpJrfUjiPQacQuCl+PMqDJWIAv7rhvhj4KQIB34o6eOSDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"efb5bd0d17f72d965475e73e6d91f20e20129f654ce3a671a1c893ef98149f4d","last_reissued_at":"2026-07-05T10:50:20.360159Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:50:20.360159Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Autonomous Drone for Dynamic Smoke Plume Tracking","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["physics.flu-dyn"],"primary_cat":"cs.RO","authors_text":"Jiarong Hong, Nikil Krishnakumar, Shashank Sharma, Srijan Kumar Pal","submitted_at":"2025-04-17T05:50:15Z","abstract_excerpt":"This paper presents a novel autonomous drone-based smoke plume tracking system capable of navigating and tracking plumes in highly unsteady atmospheric conditions. The system integrates advanced hardware and software and a comprehensive simulation environment to ensure robust performance in controlled and real-world settings. The quadrotor, equipped with a high-resolution imaging system and an advanced onboard computing unit, performs precise maneuvers while accurately detecting and tracking dynamic smoke plumes under fluctuating conditions. Our software implements a two-phase flight operation"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.12664","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2504.12664/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2504.12664","created_at":"2026-07-05T10:50:20.360220+00:00"},{"alias_kind":"arxiv_version","alias_value":"2504.12664v1","created_at":"2026-07-05T10:50:20.360220+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.12664","created_at":"2026-07-05T10:50:20.360220+00:00"},{"alias_kind":"pith_short_12","alias_value":"56232DIX64WZ","created_at":"2026-07-05T10:50:20.360220+00:00"},{"alias_kind":"pith_short_16","alias_value":"56232DIX64WZMVDV","created_at":"2026-07-05T10:50:20.360220+00:00"},{"alias_kind":"pith_short_8","alias_value":"56232DIX","created_at":"2026-07-05T10:50:20.360220+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2505.22436","citing_title":"COSMOS: A Data-Driven Probabilistic Time Series simulator for Chemical Plumes across Spatial Scales","ref_index":2,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/56232DIX64WZMVDV447G3EPSBY","json":"https://pith.science/pith/56232DIX64WZMVDV447G3EPSBY.json","graph_json":"https://pith.science/api/pith-number/56232DIX64WZMVDV447G3EPSBY/graph.json","events_json":"https://pith.science/api/pith-number/56232DIX64WZMVDV447G3EPSBY/events.json","paper":"https://pith.science/paper/56232DIX"},"agent_actions":{"view_html":"https://pith.science/pith/56232DIX64WZMVDV447G3EPSBY","download_json":"https://pith.science/pith/56232DIX64WZMVDV447G3EPSBY.json","view_paper":"https://pith.science/paper/56232DIX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2504.12664&json=true","fetch_graph":"https://pith.science/api/pith-number/56232DIX64WZMVDV447G3EPSBY/graph.json","fetch_events":"https://pith.science/api/pith-number/56232DIX64WZMVDV447G3EPSBY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/56232DIX64WZMVDV447G3EPSBY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/56232DIX64WZMVDV447G3EPSBY/action/storage_attestation","attest_author":"https://pith.science/pith/56232DIX64WZMVDV447G3EPSBY/action/author_attestation","sign_citation":"https://pith.science/pith/56232DIX64WZMVDV447G3EPSBY/action/citation_signature","submit_replication":"https://pith.science/pith/56232DIX64WZMVDV447G3EPSBY/action/replication_record"}},"created_at":"2026-07-05T10:50:20.360220+00:00","updated_at":"2026-07-05T10:50:20.360220+00:00"}