{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:21:14Z","timestamp":1750220474766,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":38,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T00:00:00Z","timestamp":1637107200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,11,17]]},"DOI":"10.1145\/3486611.3486660","type":"proceedings-article","created":{"date-parts":[[2021,11,18]],"date-time":"2021-11-18T01:24:25Z","timestamp":1637198665000},"page":"81-90","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Energy-efficient parking analytics system using deep reinforcement learning"],"prefix":"10.1145","author":[{"given":"Yoones","family":"Rezaei","sequence":"first","affiliation":[{"name":"University of Pittsburgh"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stephen","family":"Lee","sequence":"additional","affiliation":[{"name":"University of Pittsburgh"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Mosse","sequence":"additional","affiliation":[{"name":"University of Pittsburgh"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,11,17]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Debaditya Acharya Weilin Yan and Kourosh Khoshelham. 2018. Real-time image-based parking occupancy detection using deep learning.. In Research@Locate. 33--40.  Debaditya Acharya Weilin Yan and Kourosh Khoshelham. 2018. Real-time image-based parking occupancy detection using deep learning.. In Research@Locate. 33--40."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.10.055"},{"key":"e_1_3_2_1_3_1","volume-title":"Real-time video analytics: The killer app for edge computing. computer 50, 10","author":"Ananthanarayanan Ganesh","year":"2017","unstructured":"Ganesh Ananthanarayanan , Paramvir Bahl , Peter Bod\u00edk , Krishna Chintalapudi , Matthai Philipose , Lenin Ravindranath , and Sudipta Sinha . 2017. Real-time video analytics: The killer app for edge computing. computer 50, 10 ( 2017 ), 58--67. Ganesh Ananthanarayanan, Paramvir Bahl, Peter Bod\u00edk, Krishna Chintalapudi, Matthai Philipose, Lenin Ravindranath, and Sudipta Sinha. 2017. Real-time video analytics: The killer app for edge computing. computer 50, 10 (2017), 58--67."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jue.2006.04.004"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/IoTDI49375.2020.00015"},{"key":"e_1_3_2_1_6_1","unstructured":"Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang and Wojciech Zaremba. 2016. OpenAI Gym. arXiv:arXiv:1606.01540  Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang and Wojciech Zaremba. 2016. OpenAI Gym. arXiv:arXiv:1606.01540"},{"key":"e_1_3_2_1_7_1","unstructured":"Francois Chollet et al. 2015. Keras. https:\/\/github.com\/fchollet\/keras  Francois Chollet et al. 2015. Keras. https:\/\/github.com\/fchollet\/keras"},{"key":"e_1_3_2_1_8_1","volume-title":"IHS Markit Says","author":"Surveillance Consumer Video","year":"2018","unstructured":"Consumer Video Surveillance Market to Top $1 Billion in 2018 , IHS Markit Says . 2018 . Consumer Video Surveillance Market to Top $1 Billion in 2018, IHS Markit Says . https:\/\/bit.ly\/30XBt5C. Consumer Video Surveillance Market to Top $1 Billion in 2018, IHS Markit Says. 2018. Consumer Video Surveillance Market to Top $1 Billion in 2018, IHS Markit Says. https:\/\/bit.ly\/30XBt5C."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3360322.3360857"},{"key":"e_1_3_2_1_10_1","volume-title":"Aces: Automatic configuration of energy harvesting sensors with reinforcement learning. ACM Transactions on Sensor Networks (TOSN)","author":"Fraternali Francesco","year":"2020","unstructured":"Francesco Fraternali , Bharathan Balaji , Yuvraj Agarwal , and Rajesh K Gupta . 2020 . Aces: Automatic configuration of energy harvesting sensors with reinforcement learning. ACM Transactions on Sensor Networks (TOSN) (2020). Francesco Fraternali, Bharathan Balaji, Yuvraj Agarwal, and Rajesh K Gupta. 2020. Aces: Automatic configuration of energy harvesting sensors with reinforcement learning. ACM Transactions on Sensor Networks (TOSN) (2020)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3384419.3430468"},{"key":"e_1_3_2_1_12_1","volume-title":"Energy efficiency of the Internet of Things. Technology and Energy Assessment Report prepared for IEA 4E EDNA","author":"Friedli Martin","year":"2016","unstructured":"Martin Friedli , Lukas Kaufmann , Francesco Paganini , and Rainer Kyburz . 2016. Energy efficiency of the Internet of Things. Technology and Energy Assessment Report prepared for IEA 4E EDNA . Lucerne University of Applied Sciences , Switzerland ( 2016 ). Martin Friedli, Lukas Kaufmann, Francesco Paganini, and Rainer Kyburz. 2016. Energy efficiency of the Internet of Things. Technology and Energy Assessment Report prepared for IEA 4E EDNA. Lucerne University of Applied Sciences, Switzerland (2016)."},{"key":"e_1_3_2_1_13_1","unstructured":"Google. 2020. Google Nest. https:\/\/nest.com\/.  Google. 2020. Google Nest. https:\/\/nest.com\/."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3230543.3230574"},{"key":"e_1_3_2_1_15_1","volume-title":"Noscope: optimizing neural network queries over video at scale. arXiv preprint arXiv:1703.02529","author":"Kang Daniel","year":"2017","unstructured":"Daniel Kang , John Emmons , Firas Abuzaid , Peter Bailis , and Matei Zaharia . 2017. Noscope: optimizing neural network queries over video at scale. arXiv preprint arXiv:1703.02529 ( 2017 ). Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, and Matei Zaharia. 2017. Noscope: optimizing neural network queries over video at scale. arXiv preprint arXiv:1703.02529 (2017)."},{"key":"e_1_3_2_1_16_1","volume-title":"An efficient k-means clustering algorithm: Analysis and implementation","author":"Kanungo Tapas","year":"2002","unstructured":"Tapas Kanungo , David M Mount , Nathan S Netanyahu , Christine D Piatko , Ruth Silverman , and Angela Y Wu. 2002. An efficient k-means clustering algorithm: Analysis and implementation . IEEE transactions on pattern analysis and machine intelligence 24, 7 ( 2002 ), 881--892. Tapas Kanungo, David M Mount, Nathan S Netanyahu, Christine D Piatko, Ruth Silverman, and Angela Y Wu. 2002. An efficient k-means clustering algorithm: Analysis and implementation. IEEE transactions on pattern analysis and machine intelligence 24, 7 (2002), 881--892."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/THMS.2013.2285921"},{"volume-title":"Proceeding of the 11th annual international conference on Mobile systems, applications, and services. 69--82.","author":"LiKamWa Robert","key":"e_1_3_2_1_18_1","unstructured":"Robert LiKamWa , Bodhi Priyantha , Matthai Philipose , Lin Zhong , and Paramvir Bahl . 2013. Energy characterization and optimization of image sensing toward continuous mobile vision . In Proceeding of the 11th annual international conference on Mobile systems, applications, and services. 69--82. Robert LiKamWa, Bodhi Priyantha, Matthai Philipose, Lin Zhong, and Paramvir Bahl. 2013. Energy characterization and optimization of image sensing toward continuous mobile vision. In Proceeding of the 11th annual international conference on Mobile systems, applications, and services. 69--82."},{"key":"e_1_3_2_1_19_1","volume-title":"Brief Presentations Proceedings (RTAS 2019)","author":"Luo Yubo","year":"2019","unstructured":"Yubo Luo and Shahriar Nirjon . 2019 . Spoton: Just-in-time active event detection on energy autonomous sensing systems . Brief Presentations Proceedings (RTAS 2019) 9 (2019). Yubo Luo and Shahriar Nirjon. 2019. Spoton: Just-in-time active event detection on energy autonomous sensing systems. Brief Presentations Proceedings (RTAS 2019) 9 (2019)."},{"key":"e_1_3_2_1_20_1","unstructured":"Kevin McCoy. 2017. Drivers spend an average of 17 hours a year searching for parking spots. https:\/\/bit.ly\/36Y2VlU.  Kevin McCoy. 2017. Drivers spend an average of 17 hours a year searching for parking spots. https:\/\/bit.ly\/36Y2VlU."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Volodymyr Mnih Koray Kavukcuoglu David Silver Andrei A Rusu Joel Veness Marc G Bellemare Alex Graves Martin Riedmiller Andreas K Fidjeland Georg Ostrovski etal 2015. Human-level control through deep reinforcement learning. nature 518 7540 (2015) 529--533.  Volodymyr Mnih Koray Kavukcuoglu David Silver Andrei A Rusu Joel Veness Marc G Bellemare Alex Graves Martin Riedmiller Andreas K Fidjeland Georg Ostrovski et al. 2015. Human-level control through deep reinforcement learning. nature 518 7540 (2015) 529--533.","DOI":"10.1038\/nature14236"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2009.158"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISCA.2018.00063"},{"key":"e_1_3_2_1_24_1","volume-title":"Prioritized experience replay. arXiv preprint arXiv:1511.05952","author":"Schaul Tom","year":"2015","unstructured":"Tom Schaul , John Quan , Ioannis Antonoglou , and David Silver . 2015. Prioritized experience replay. arXiv preprint arXiv:1511.05952 ( 2015 ). Tom Schaul, John Quan, Ioannis Antonoglou, and David Silver. 2015. Prioritized experience replay. arXiv preprint arXiv:1511.05952 (2015)."},{"key":"e_1_3_2_1_25_1","volume-title":"Green ai. arXiv preprint arXiv:1907.10597","author":"Schwartz Roy","year":"2019","unstructured":"Roy Schwartz , Jesse Dodge , Noah A Smith , and Oren Etzioni . 2019. Green ai. arXiv preprint arXiv:1907.10597 ( 2019 ). Roy Schwartz, Jesse Dodge, Noah A Smith, and Oren Etzioni. 2019. Green ai. arXiv preprint arXiv:1907.10597 (2019)."},{"key":"e_1_3_2_1_26_1","unstructured":"Donald Shoup. 2011. The high cost of free parking. American planning association.  Donald Shoup. 2011. The high cost of free parking. American planning association."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/1067170.1067198"},{"volume-title":"Reinforcement learning: An introduction","author":"Sutton Richard S","key":"e_1_3_2_1_28_1","unstructured":"Richard S Sutton and Andrew G Barto . 2018. Reinforcement learning: An introduction . MIT press . Richard S Sutton and Andrew G Barto. 2018. Reinforcement learning: An introduction. MIT press."},{"key":"e_1_3_2_1_29_1","unstructured":"The city of Melbourne Parking dataset. 2019. https:\/\/bit.ly\/3ESojsi.  The city of Melbourne Parking dataset. 2019. https:\/\/bit.ly\/3ESojsi."},{"volume-title":"Parking-stall vacancy indicator system, based on deep convolutional neural networks. In 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT)","author":"Valipour Sepehr","key":"e_1_3_2_1_30_1","unstructured":"Sepehr Valipour , Mennatullah Siam , Eleni Stroulia , and Martin Jagersand . 2016. Parking-stall vacancy indicator system, based on deep convolutional neural networks. In 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT) . IEEE. Sepehr Valipour, Mennatullah Siam, Eleni Stroulia, and Martin Jagersand. 2016. Parking-stall vacancy indicator system, based on deep convolutional neural networks. In 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT). IEEE."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.5555\/3016100.3016191"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/IoTDI49375.2020.00024"},{"key":"e_1_3_2_1_33_1","volume-title":"International conference on machine learning. 1995--2003","author":"Wang Ziyu","year":"2016","unstructured":"Ziyu Wang , Tom Schaul , Matteo Hessel , Hado Hasselt , Marc Lanctot , and Nando Freitas . 2016 . Dueling network architectures for deep reinforcement learning . In International conference on machine learning. 1995--2003 . Ziyu Wang, Tom Schaul, Matteo Hessel, Hado Hasselt, Marc Lanctot, and Nando Freitas. 2016. Dueling network architectures for deep reinforcement learning. In International conference on machine learning. 1995--2003."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-94268-1_40"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2003.815165"},{"key":"e_1_3_2_1_36_1","volume-title":"Towards monocular vision based obstacle avoidance through deep reinforcement learning. arXiv preprint arXiv:1706.09829","author":"Xie Linhai","year":"2017","unstructured":"Linhai Xie , Sen Wang , Andrew Markham , and Niki Trigoni . 2017. Towards monocular vision based obstacle avoidance through deep reinforcement learning. arXiv preprint arXiv:1706.09829 ( 2017 ). Linhai Xie, Sen Wang, Andrew Markham, and Niki Trigoni. 2017. Towards monocular vision based obstacle avoidance through deep reinforcement learning. arXiv preprint arXiv:1706.09829 (2017)."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3386901.3388948"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1002\/smll.201802188"}],"event":{"name":"BuildSys '21: The 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","sponsor":["SIGEnergy ACM Special Interest Group on Energy Systems and Informatics"],"location":"Coimbra Portugal","acronym":"BuildSys '21"},"container-title":["Proceedings of the 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3486611.3486660","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3486611.3486660","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:48:40Z","timestamp":1750193320000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3486611.3486660"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,17]]},"references-count":38,"alternative-id":["10.1145\/3486611.3486660","10.1145\/3486611"],"URL":"https:\/\/doi.org\/10.1145\/3486611.3486660","relation":{},"subject":[],"published":{"date-parts":[[2021,11,17]]},"assertion":[{"value":"2021-11-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}