{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:BCBTXPT7ZGROZR6J2B5QM6E64F","short_pith_number":"pith:BCBTXPT7","schema_version":"1.0","canonical_sha256":"08833bbe7fc9a2ecc7c9d07b06789ee17fcebd42dac1e96f7adbd312e6d11f3a","source":{"kind":"arxiv","id":"2509.02869","version":1},"attestation_state":"computed","paper":{"title":"A Distributed Gradient-Based Deployment Strategy for a Network of Sensors with a Probabilistic Sensing Model","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Amir G. Aghdam, Hesam Mosalli","submitted_at":"2025-09-02T22:34:41Z","abstract_excerpt":"This paper presents a distributed gradient-based deployment strategy to maximize coverage in hybrid wireless sensor networks (WSNs) with probabilistic sensing. Leveraging Voronoi partitioning, the overall coverage is reformulated as a sum of local contributions, enabling mobile sensors to optimize their positions using only local information. The strategy adopts the Elfes model to capture detection uncertainty and introduces a dynamic step size based on the gradient of the local coverage, ensuring movements adaptive to regional importance. Obstacle awareness is integrated via visibility constr"},"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":"2509.02869","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.SY","submitted_at":"2025-09-02T22:34:41Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"9318fe137721bde1262ecbf99f6cf4961700c969ec3a1853c7bc82727bdabf7b","abstract_canon_sha256":"00aed31ac9b35f2c87ad166b83ba0a336c582f7f815779305fac0db149ddff37"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:03:58.870840Z","signature_b64":"tlkPYJYn3pqdIJAo47Z9A7V29YxAHYP4L65HqrvZoky9Qy7tk2+zgjrAb3hO0IUYuUUbkD6qcr0/Tj5fnbVZDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"08833bbe7fc9a2ecc7c9d07b06789ee17fcebd42dac1e96f7adbd312e6d11f3a","last_reissued_at":"2026-07-05T12:03:58.870312Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:03:58.870312Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Distributed Gradient-Based Deployment Strategy for a Network of Sensors with a Probabilistic Sensing Model","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Amir G. Aghdam, Hesam Mosalli","submitted_at":"2025-09-02T22:34:41Z","abstract_excerpt":"This paper presents a distributed gradient-based deployment strategy to maximize coverage in hybrid wireless sensor networks (WSNs) with probabilistic sensing. Leveraging Voronoi partitioning, the overall coverage is reformulated as a sum of local contributions, enabling mobile sensors to optimize their positions using only local information. The strategy adopts the Elfes model to capture detection uncertainty and introduces a dynamic step size based on the gradient of the local coverage, ensuring movements adaptive to regional importance. Obstacle awareness is integrated via visibility constr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.02869","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/2509.02869/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":"2509.02869","created_at":"2026-07-05T12:03:58.870382+00:00"},{"alias_kind":"arxiv_version","alias_value":"2509.02869v1","created_at":"2026-07-05T12:03:58.870382+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.02869","created_at":"2026-07-05T12:03:58.870382+00:00"},{"alias_kind":"pith_short_12","alias_value":"BCBTXPT7ZGRO","created_at":"2026-07-05T12:03:58.870382+00:00"},{"alias_kind":"pith_short_16","alias_value":"BCBTXPT7ZGROZR6J","created_at":"2026-07-05T12:03:58.870382+00:00"},{"alias_kind":"pith_short_8","alias_value":"BCBTXPT7","created_at":"2026-07-05T12:03:58.870382+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/BCBTXPT7ZGROZR6J2B5QM6E64F","json":"https://pith.science/pith/BCBTXPT7ZGROZR6J2B5QM6E64F.json","graph_json":"https://pith.science/api/pith-number/BCBTXPT7ZGROZR6J2B5QM6E64F/graph.json","events_json":"https://pith.science/api/pith-number/BCBTXPT7ZGROZR6J2B5QM6E64F/events.json","paper":"https://pith.science/paper/BCBTXPT7"},"agent_actions":{"view_html":"https://pith.science/pith/BCBTXPT7ZGROZR6J2B5QM6E64F","download_json":"https://pith.science/pith/BCBTXPT7ZGROZR6J2B5QM6E64F.json","view_paper":"https://pith.science/paper/BCBTXPT7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2509.02869&json=true","fetch_graph":"https://pith.science/api/pith-number/BCBTXPT7ZGROZR6J2B5QM6E64F/graph.json","fetch_events":"https://pith.science/api/pith-number/BCBTXPT7ZGROZR6J2B5QM6E64F/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BCBTXPT7ZGROZR6J2B5QM6E64F/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BCBTXPT7ZGROZR6J2B5QM6E64F/action/storage_attestation","attest_author":"https://pith.science/pith/BCBTXPT7ZGROZR6J2B5QM6E64F/action/author_attestation","sign_citation":"https://pith.science/pith/BCBTXPT7ZGROZR6J2B5QM6E64F/action/citation_signature","submit_replication":"https://pith.science/pith/BCBTXPT7ZGROZR6J2B5QM6E64F/action/replication_record"}},"created_at":"2026-07-05T12:03:58.870382+00:00","updated_at":"2026-07-05T12:03:58.870382+00:00"}