{"id":"W4313270307","doi":"10.1109/icirca54612.2022.9985762","title":"Implementation of Smart Vehicle Accident Detection using Raspberry PI in Smart Cities","year":2022,"lang":"en","type":"article","venue":"2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA)","topic":"IoT and GPS-based Vehicle Safety Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Raspberry pi; Global Positioning System; Geographic coordinate system; GSM; Computer science; Real-time computing; Computer security; Accident (philosophy); Emergency vehicle; Embedded system; Telecommunications; Internet of Things; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004099899,0.0004549933,0.0003080196,0.0006620529,0.0003285987,0.0006013448,0.0006858874,0.0004880355,0.002434504],"category_scores_gemma":[0.0007101907,0.0002566536,0.0002813452,0.0003872296,0.0002190459,0.0007027176,0.0004998847,0.0003562309,0.0009818967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003272478,"about_ca_system_score_gemma":0.0006362167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004920299,"about_ca_topic_score_gemma":0.003076732,"domain_scores_codex":[0.9995035,0.00009198509,0.00003271635,0.0001202501,0.0001388956,0.0001126051],"domain_scores_gemma":[0.9995325,0.00005519268,0.00004649267,0.00008372537,0.0002186744,0.00006347866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00132156,0.001332748,0.05321695,0.0006265649,0.0001889213,0.001613503,0.001637814,0.06247587,0.1729307,0.006539497,0.0102776,0.6878384],"study_design_scores_gemma":[0.0003679855,0.00234607,0.06492566,0.00009831536,0.0003155424,0.0008654413,0.001596758,0.5819758,0.2940328,0.002265914,0.05097419,0.0002355636],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6375477,0.0002398405,0.3196541,0.0005745605,0.0002315533,0.0007558653,0.0003989821,0.01894697,0.02165043],"genre_scores_gemma":[0.950122,0.0000888377,0.044943,0.0000613622,0.00001051249,0.0001266915,0.0001560528,0.00004710033,0.00444433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004920299,"threshold_uncertainty_score":0.009783328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.12795747060936,"score_gpt":0.4012229239236812,"score_spread":0.2732654533143212,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}