{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:4CBAZVW2QFFSLRS4PQRS2JHZHO","short_pith_number":"pith:4CBAZVW2","schema_version":"1.0","canonical_sha256":"e0820cd6da814b25c65c7c232d24f93ba941aeb1a0e327adfb6dd05b5daf4fd1","source":{"kind":"arxiv","id":"2405.02316","version":1},"attestation_state":"computed","paper":{"title":"A Cloud-Edge Framework for Energy-Efficient Event-Driven Control: An Integration of Online Supervised Learning, Spiking Neural Networks and Local Plasticity Rules","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.NE","cs.SY"],"primary_cat":"eess.SY","authors_text":"Reza Ahmadvand, Sarah Safura Sharif, Yaser Mike Banad","submitted_at":"2024-04-12T22:34:17Z","abstract_excerpt":"This paper presents a novel cloud-edge framework for addressing computational and energy constraints in complex control systems. Our approach centers around a learning-based controller using Spiking Neural Networks (SNN) on physical plants. By integrating a biologically plausible learning method with local plasticity rules, we harness the efficiency, scalability, and low latency of SNNs. This design replicates control signals from a cloud-based controller directly on the plant, reducing the need for constant plant-cloud communication. The plant updates weights only when errors surpass predefin"},"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":"2405.02316","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2024-04-12T22:34:17Z","cross_cats_sorted":["cs.AI","cs.LG","cs.NE","cs.SY"],"title_canon_sha256":"3bfc8c5b3e6677d4a8e539287a22535a28f3c81df7a4a165ad129e56e01268a2","abstract_canon_sha256":"85776e9599cf8d72db422900c8da59d9bcaf94dd62ba3e5804125a068af565c7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:15:13.782466Z","signature_b64":"Z9iGM5U7gE73Rj8TwdROaAWc5LURVXUOGbfMcEfRS1Od3dlZWAC5f7oM/ywS6TD/AuNKU0DQjPCBeza05yDxBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e0820cd6da814b25c65c7c232d24f93ba941aeb1a0e327adfb6dd05b5daf4fd1","last_reissued_at":"2026-07-05T08:15:13.781988Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:15:13.781988Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Cloud-Edge Framework for Energy-Efficient Event-Driven Control: An Integration of Online Supervised Learning, Spiking Neural Networks and Local Plasticity Rules","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.NE","cs.SY"],"primary_cat":"eess.SY","authors_text":"Reza Ahmadvand, Sarah Safura Sharif, Yaser Mike Banad","submitted_at":"2024-04-12T22:34:17Z","abstract_excerpt":"This paper presents a novel cloud-edge framework for addressing computational and energy constraints in complex control systems. Our approach centers around a learning-based controller using Spiking Neural Networks (SNN) on physical plants. By integrating a biologically plausible learning method with local plasticity rules, we harness the efficiency, scalability, and low latency of SNNs. This design replicates control signals from a cloud-based controller directly on the plant, reducing the need for constant plant-cloud communication. The plant updates weights only when errors surpass predefin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.02316","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/2405.02316/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":"2405.02316","created_at":"2026-07-05T08:15:13.782044+00:00"},{"alias_kind":"arxiv_version","alias_value":"2405.02316v1","created_at":"2026-07-05T08:15:13.782044+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.02316","created_at":"2026-07-05T08:15:13.782044+00:00"},{"alias_kind":"pith_short_12","alias_value":"4CBAZVW2QFFS","created_at":"2026-07-05T08:15:13.782044+00:00"},{"alias_kind":"pith_short_16","alias_value":"4CBAZVW2QFFSLRS4","created_at":"2026-07-05T08:15:13.782044+00:00"},{"alias_kind":"pith_short_8","alias_value":"4CBAZVW2","created_at":"2026-07-05T08:15:13.782044+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/4CBAZVW2QFFSLRS4PQRS2JHZHO","json":"https://pith.science/pith/4CBAZVW2QFFSLRS4PQRS2JHZHO.json","graph_json":"https://pith.science/api/pith-number/4CBAZVW2QFFSLRS4PQRS2JHZHO/graph.json","events_json":"https://pith.science/api/pith-number/4CBAZVW2QFFSLRS4PQRS2JHZHO/events.json","paper":"https://pith.science/paper/4CBAZVW2"},"agent_actions":{"view_html":"https://pith.science/pith/4CBAZVW2QFFSLRS4PQRS2JHZHO","download_json":"https://pith.science/pith/4CBAZVW2QFFSLRS4PQRS2JHZHO.json","view_paper":"https://pith.science/paper/4CBAZVW2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2405.02316&json=true","fetch_graph":"https://pith.science/api/pith-number/4CBAZVW2QFFSLRS4PQRS2JHZHO/graph.json","fetch_events":"https://pith.science/api/pith-number/4CBAZVW2QFFSLRS4PQRS2JHZHO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4CBAZVW2QFFSLRS4PQRS2JHZHO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4CBAZVW2QFFSLRS4PQRS2JHZHO/action/storage_attestation","attest_author":"https://pith.science/pith/4CBAZVW2QFFSLRS4PQRS2JHZHO/action/author_attestation","sign_citation":"https://pith.science/pith/4CBAZVW2QFFSLRS4PQRS2JHZHO/action/citation_signature","submit_replication":"https://pith.science/pith/4CBAZVW2QFFSLRS4PQRS2JHZHO/action/replication_record"}},"created_at":"2026-07-05T08:15:13.782044+00:00","updated_at":"2026-07-05T08:15:13.782044+00:00"}