{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:NQPJ3JESB7GTAKAU2DIUS22ZNI","short_pith_number":"pith:NQPJ3JES","schema_version":"1.0","canonical_sha256":"6c1e9da4920fcd302814d0d1496b596a38f0c4075757c68e24d8e12826a0be2b","source":{"kind":"arxiv","id":"2111.07552","version":1},"attestation_state":"computed","paper":{"title":"Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.RO","cs.SY"],"primary_cat":"eess.SY","authors_text":"Alice Agogino, Emerson Shoichet-Bartus, Felicity Liao, Hae Young Jang, Irving Fang, John Matranga, Ritik Batra, R. Lily Hu, Rohan Sood, Vivek Rao","submitted_at":"2021-11-15T06:13:53Z","abstract_excerpt":"Although the Industrial Internet of Things has increased the number of sensors permanently installed in industrial plants, there will be gaps in coverage due to broken sensors or sparse density in very large plants, such as in the petrochemical industry. Modern emergency response operations are beginning to use Small Unmanned Aerial Systems (sUAS) that have the ability to drop sensor robots to precise locations. sUAS can provide longer-term persistent monitoring that aerial drones are unable to provide. Despite the relatively low cost of these assets, the choice of which robotic sensing system"},"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":"2111.07552","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SY","submitted_at":"2021-11-15T06:13:53Z","cross_cats_sorted":["cs.RO","cs.SY"],"title_canon_sha256":"5c019020870f1077a7d9a2239c17063fd6107ef99b1459c26a88dbff138a02c5","abstract_canon_sha256":"2fb16bb48fcde2ca819b32a5f06aaa47b389f5663effe930f3fcec315d3463ff"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:31:41.054670Z","signature_b64":"LOjAbRCotk9DX0+Mbol1Sdm3PRoNrPwiGT0u2XbsjQwp8RZU7dsJED701XMjhCkycqli/F5Lf2S4rA/WLK6sCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6c1e9da4920fcd302814d0d1496b596a38f0c4075757c68e24d8e12826a0be2b","last_reissued_at":"2026-07-05T03:31:41.054298Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:31:41.054298Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.RO","cs.SY"],"primary_cat":"eess.SY","authors_text":"Alice Agogino, Emerson Shoichet-Bartus, Felicity Liao, Hae Young Jang, Irving Fang, John Matranga, Ritik Batra, R. Lily Hu, Rohan Sood, Vivek Rao","submitted_at":"2021-11-15T06:13:53Z","abstract_excerpt":"Although the Industrial Internet of Things has increased the number of sensors permanently installed in industrial plants, there will be gaps in coverage due to broken sensors or sparse density in very large plants, such as in the petrochemical industry. Modern emergency response operations are beginning to use Small Unmanned Aerial Systems (sUAS) that have the ability to drop sensor robots to precise locations. sUAS can provide longer-term persistent monitoring that aerial drones are unable to provide. Despite the relatively low cost of these assets, the choice of which robotic sensing system"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.07552","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/2111.07552/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":"2111.07552","created_at":"2026-07-05T03:31:41.054363+00:00"},{"alias_kind":"arxiv_version","alias_value":"2111.07552v1","created_at":"2026-07-05T03:31:41.054363+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.07552","created_at":"2026-07-05T03:31:41.054363+00:00"},{"alias_kind":"pith_short_12","alias_value":"NQPJ3JESB7GT","created_at":"2026-07-05T03:31:41.054363+00:00"},{"alias_kind":"pith_short_16","alias_value":"NQPJ3JESB7GTAKAU","created_at":"2026-07-05T03:31:41.054363+00:00"},{"alias_kind":"pith_short_8","alias_value":"NQPJ3JES","created_at":"2026-07-05T03:31:41.054363+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/NQPJ3JESB7GTAKAU2DIUS22ZNI","json":"https://pith.science/pith/NQPJ3JESB7GTAKAU2DIUS22ZNI.json","graph_json":"https://pith.science/api/pith-number/NQPJ3JESB7GTAKAU2DIUS22ZNI/graph.json","events_json":"https://pith.science/api/pith-number/NQPJ3JESB7GTAKAU2DIUS22ZNI/events.json","paper":"https://pith.science/paper/NQPJ3JES"},"agent_actions":{"view_html":"https://pith.science/pith/NQPJ3JESB7GTAKAU2DIUS22ZNI","download_json":"https://pith.science/pith/NQPJ3JESB7GTAKAU2DIUS22ZNI.json","view_paper":"https://pith.science/paper/NQPJ3JES","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2111.07552&json=true","fetch_graph":"https://pith.science/api/pith-number/NQPJ3JESB7GTAKAU2DIUS22ZNI/graph.json","fetch_events":"https://pith.science/api/pith-number/NQPJ3JESB7GTAKAU2DIUS22ZNI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NQPJ3JESB7GTAKAU2DIUS22ZNI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NQPJ3JESB7GTAKAU2DIUS22ZNI/action/storage_attestation","attest_author":"https://pith.science/pith/NQPJ3JESB7GTAKAU2DIUS22ZNI/action/author_attestation","sign_citation":"https://pith.science/pith/NQPJ3JESB7GTAKAU2DIUS22ZNI/action/citation_signature","submit_replication":"https://pith.science/pith/NQPJ3JESB7GTAKAU2DIUS22ZNI/action/replication_record"}},"created_at":"2026-07-05T03:31:41.054363+00:00","updated_at":"2026-07-05T03:31:41.054363+00:00"}