{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T19:45:35Z","timestamp":1786391135438,"version":"build-2736575974"},"publisher-location":"New York, NY, USA","reference-count":53,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T00:00:00Z","timestamp":1785888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-2211301"],"award-info":[{"award-number":["CNS-2211301"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-2211302"],"award-info":[{"award-number":["CNS-2211302"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-2213636"],"award-info":[{"award-number":["CNS-2213636"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-2325956"],"award-info":[{"award-number":["CNS-2325956"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100019923","name":"DEVCOM Army Research Laboratory","doi-asserted-by":"publisher","award":["W911NF1720196"],"award-info":[{"award-number":["W911NF1720196"]}],"id":[{"id":"10.13039\/100019923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,8,5]]},"DOI":"10.1145\/3816440.3818532","type":"proceedings-article","created":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T19:23:31Z","timestamp":1786389811000},"page":"1-7","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["FM-CAC: Carbon-Aware Control for Battery-Buffered Edge AI via Time-Series Foundation Models"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8248-4894","authenticated-orcid":false,"given":"Kang","family":"Yang","sequence":"first","affiliation":[{"name":"University of California, Los Angeles, Los Angeles, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5765-8194","authenticated-orcid":false,"given":"Walid A.","family":"Hanafy","sequence":"additional","affiliation":[{"name":"University of Massachusetts, Amherst, Amherst, --, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5435-1901","authenticated-orcid":false,"given":"Prashant","family":"Shenoy","sequence":"additional","affiliation":[{"name":"University of Massachusetts, Amherst, Amherst, --, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3782-9192","authenticated-orcid":false,"given":"Mani","family":"Srivastava","sequence":"additional","affiliation":[{"name":"University of California, Los Angeles, Los Angeles, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,8,10]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2022.3173250"},{"key":"e_1_3_2_1_2_1","volume-title":"State of IoT 2025: Number of Connected IoT Devices Growing 14% to 21.1 Billion Globally. https:\/\/iot-analytics.com\/number-connected-iot-devices\/","author":"Analytics T","year":"2025","unstructured":"IoT Analytics. State of IoT 2025: Number of Connected IoT Devices Growing 14% to 21.1 Billion Globally. https:\/\/iot-analytics.com\/number-connected-iot-devices\/, 2025. [Online]."},{"key":"e_1_3_2_1_3_1","volume-title":"How Many Smartphones Are in the World? https:\/\/www.bankmycell.com\/blog\/how-many-phones-are-in-the-world","year":"2026","unstructured":"BankMyCell. How Many Smartphones Are in the World? https:\/\/www.bankmycell.com\/blog\/how-many-phones-are-in-the-world, 2026. [Online]."},{"key":"e_1_3_2_1_4_1","volume-title":"How Many Surveillance Cameras Are Installed Every Day? https:\/\/anythingcounter.com\/surveillance-cameras-installed-per-day","year":"2025","unstructured":"AnythingCounter. How Many Surveillance Cameras Are Installed Every Day? https:\/\/anythingcounter.com\/surveillance-cameras-installed-per-day, 2025. [Online]."},{"key":"e_1_3_2_1_5_1","volume-title":"Greenhouse Gas Emissions from a Typical Passenger Vehicle. https:\/\/www.epa.gov\/greenvehicles\/greenhouse-gas-emissions-typical-passenger-vehicle","author":"U.S. Environmental Protection Agency (EPA).","year":"2023","unstructured":"U.S. Environmental Protection Agency (EPA). Greenhouse Gas Emissions from a Typical Passenger Vehicle. https:\/\/www.epa.gov\/greenvehicles\/greenhouse-gas-emissions-typical-passenger-vehicle, 2023. [Online]."},{"key":"e_1_3_2_1_6_1","volume-title":"Statues: Energy-Efficient Video Object Detection on Edge Security Devices with Computational Skipping","author":"Kim Yeonggeon","year":"2024","unstructured":"Yeonggeon Kim, Hyunmin Kim, and Sungju Ryu. Statues: Energy-Efficient Video Object Detection on Edge Security Devices with Computational Skipping. In ACM\/IEEE ISLPED, 2024."},{"key":"e_1_3_2_1_7_1","volume-title":"Nest Cam with Floodlight Technical Specs. https:\/\/store.google.com\/product\/nest_cam_floodlight_specs","year":"2024","unstructured":"Google. Nest Cam with Floodlight Technical Specs. https:\/\/store.google.com\/product\/nest_cam_floodlight_specs, 2024. [Online]."},{"key":"e_1_3_2_1_8_1","volume-title":"The Shift from Models to Compound AI Systems. https:\/\/bair.berkeley.edu\/blog\/2024\/02\/18\/compound-ai-systems\/","author":"Matei Zaharia","year":"2024","unstructured":"Matei Zaharia et al. The Shift from Models to Compound AI Systems. https:\/\/bair.berkeley.edu\/blog\/2024\/02\/18\/compound-ai-systems\/, 2024. [Online]."},{"key":"e_1_3_2_1_9_1","volume-title":"Navigating Battery Choices in IoT: An Extensive Survey of Technologies and Their Applications. Batteries, 9(12)","author":"Hasan Kareeb","year":"2023","unstructured":"Kareeb Hasan, Neil Tom, and Mehmet Rasit Yuce. Navigating Battery Choices in IoT: An Extensive Survey of Technologies and Their Applications. Batteries, 9(12), 2023."},{"key":"e_1_3_2_1_10_1","volume-title":"KONA Micro IoT Gateway. https:\/\/tektelic.com\/products\/gateways\/kona-micro-iot-gateway\/","author":"Communications TEKTELIC","year":"2024","unstructured":"TEKTELIC Communications. KONA Micro IoT Gateway. https:\/\/tektelic.com\/products\/gateways\/kona-micro-iot-gateway\/, 2024. [Online]."},{"key":"e_1_3_2_1_11_1","volume-title":"Energy-Aware Dynamic Neural Inference. arXiv preprint arXiv:2411.02471","author":"Bullo Marcello","year":"2024","unstructured":"Marcello Bullo, Seifallah Jardak, Pietro Carnelli, and Deniz G\u00fcnd\u00fcz. Energy-Aware Dynamic Neural Inference. arXiv preprint arXiv:2411.02471, 2024."},{"key":"e_1_3_2_1_12_1","volume-title":"AAAI","author":"Zhang Ziyang","year":"2025","unstructured":"Ziyang Zhang, Yang Zhao, Ming-Ching Chang, Changyao Lin, and Jie Liu. E4: Energy-Efficient DNN Inference for Edge Video Analytics via Early Exiting and DVFS. In AAAI, 2025."},{"key":"e_1_3_2_1_13_1","volume-title":"ACM MobiSys","author":"Jeon Seunghyeok","year":"2023","unstructured":"Seunghyeok Jeon, Yonghun Choi, Yeonwoo Cho, and Hojung Cha. HarvNet: Resource-Optimized Operation of Multi-Exit Deep Neural Networks on Energy Harvesting Devices. In ACM MobiSys, 2023."},{"key":"e_1_3_2_1_14_1","volume-title":"IEEE ICC","author":"Han Yunchu","year":"2025","unstructured":"Yunchu Han, Zhaojun Nan, Sheng Zhou, and Zhisheng Niu. DVFS-Aware DNN Inference on GPUs: Latency Modeling and Performance Analysis. In IEEE ICC, 2025."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3482288"},{"key":"e_1_3_2_1_16_1","volume-title":"Energy Efficient and QoS-Aware Model Selection for DNN Inference in Edge Intelligence","author":"Siar Hajar","year":"2025","unstructured":"Hajar Siar and Erik Elmroth. Energy Efficient and QoS-Aware Model Selection for DNN Inference in Edge Intelligence. In IEEE CloudCom, 2025."},{"key":"e_1_3_2_1_17_1","volume-title":"Greening Edge AI: Optimizing Inference Accuracy and Reducing Carbon Emissions with Renewable Energy","author":"Ma Huirong","year":"2025","unstructured":"Huirong Ma, Zhilan Huang, Gang Lu, Deji Fu, and Chunyu Shi. Greening Edge AI: Optimizing Inference Accuracy and Reducing Carbon Emissions with Renewable Energy. IEEE Internet of Things Journal, 2025."},{"key":"e_1_3_2_1_18_1","volume-title":"Does Energy-Efficiency Mean Carbon-Awareness? A Critical Evaluation of Sustainable Serverless Edge Scheduling","author":"Zhu Shaoshu","year":"2025","unstructured":"Shaoshu Zhu, Neil Hurley, and Hadi Tabatabaee Malazi. Does Energy-Efficiency Mean Carbon-Awareness? A Critical Evaluation of Sustainable Serverless Edge Scheduling. In IEEE\/ACM UCC, 2025."},{"key":"e_1_3_2_1_19_1","volume-title":"Adaptive Duty Cycling for Energy Harvesting Systems","author":"Hsu Jason","year":"2006","unstructured":"Jason Hsu, Sadaf Zahedi, Aman Kansal, Mani Srivastava, and Vijay Raghunathan. Adaptive Duty Cycling for Energy Harvesting Systems. In ACM\/IEEE ISLPED, 2006."},{"key":"e_1_3_2_1_20_1","volume-title":"CLOVER: Carbon Optimization of Federated Learning over Heterogeneous Clients","author":"Cho Chanwoo","year":"2024","unstructured":"Chanwoo Cho, Yonglak Son, Seongbin Park, and Young Geun Kim. CLOVER: Carbon Optimization of Federated Learning over Heterogeneous Clients. In ACM\/IEEE ISLPED, 2024."},{"key":"e_1_3_2_1_21_1","volume-title":"ACM Middleware","author":"Wiesner Philipp","year":"2021","unstructured":"Philipp Wiesner, Ilja Behnke, Dominik Scheinert, Kordian Gontarska, and Lauritz Thamsen. Let's Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud. In ACM Middleware, 2021."},{"key":"e_1_3_2_1_22_1","volume-title":"HotCarbon","author":"Maji Diptyaroop","year":"2023","unstructured":"Diptyaroop Maji, Ben Pfaff, Vipin PR, Rajagopal Sreenivasan, Victor Firoiu, Sreeram Iyer, Colleen Josephson, Zhelong Pan, and Ramesh K Sitaraman. Bringing Carbon Awareness to Multi-Cloud Application Delivery. In HotCarbon, 2023."},{"key":"e_1_3_2_1_23_1","volume-title":"Baolin Li, and Devesh Tiwari. EcoLife: Carbon-Aware Serverless Function Scheduling for Sustainable Computing","author":"Jiang Yankai","year":"2024","unstructured":"Yankai Jiang, Rohan Basu Roy, Baolin Li, and Devesh Tiwari. EcoLife: Carbon-Aware Serverless Function Scheduling for Sustainable Computing. In ACM\/IEEE SC, 2024."},{"key":"e_1_3_2_1_24_1","volume-title":"GreenScale: Carbon-Aware Systems for Edge Computing. arXiv preprint arXiv:2304.00404","author":"Kim Young Geun","year":"2023","unstructured":"Young Geun Kim, Udit Gupta, Andrew McCrabb, Yonglak Son, Valeria Bertacco, David Brooks, and Carole-Jean Wu. GreenScale: Carbon-Aware Systems for Edge Computing. arXiv preprint arXiv:2304.00404, 2023."},{"key":"e_1_3_2_1_25_1","volume-title":"IEEE ICDCS","author":"Su Shuomiao","year":"2023","unstructured":"Shuomiao Su, Zhi Zhou, Tao Ouyang, Ruiting Zhou, and Xu Chen. Learning to Be Green: Carbon-Aware Online Control for Edge Intelligence with Colocated Learning and Inference. In IEEE ICDCS, 2023."},{"key":"e_1_3_2_1_26_1","volume-title":"Online Smoothed Demand Management. arXiv preprint arXiv:2511.18554","author":"Lechowicz Adam","year":"2025","unstructured":"Adam Lechowicz, Nicolas Christianson, Mohammad Hajiesmaili, Adam Wierman, and Prashant Shenoy. Online Smoothed Demand Management. arXiv preprint arXiv:2511.18554, 2025."},{"key":"e_1_3_2_1_27_1","volume-title":"Will Smart Prices Induce Smart Charging of Electric Vehicles? https:\/\/www.brattle.com\/wp-content\/uploads\/2017\/10\/6368_will_smart_prices_induce_smart_charging_of_electric_vehicles_jul_2011.pdf","author":"Faruqui Ahmad","year":"2011","unstructured":"Ahmad Faruqui and Sanem Sergici. Will Smart Prices Induce Smart Charging of Electric Vehicles? https:\/\/www.brattle.com\/wp-content\/uploads\/2017\/10\/6368_will_smart_prices_induce_smart_charging_of_electric_vehicles_jul_2011.pdf, 2011. [Online]."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"crossref","first-page":"8225","DOI":"10.1016\/j.egyr.2022.06.048","article-title":"Impact of Electric Vehicle Customer Response to Time-Of-Use Rates on Distribution Power Grids","volume":"8","author":"Jones C Birk","year":"2022","unstructured":"C Birk Jones, William Vining, Matthew Lave, Thad Haines, Christopher Neuman, Jesse Bennett, and Don R Scoffield. Impact of Electric Vehicle Customer Response to Time-Of-Use Rates on Distribution Power Grids. Energy Reports, 8:8225\u20138235, 2022.","journal-title":"Energy Reports"},{"key":"e_1_3_2_1_29_1","volume-title":"Carbon-Aware EV Charging","author":"Cheng Kai-Wen","year":"2022","unstructured":"Kai-Wen Cheng, Yuexin Bian, Yuanyuan Shi, and Yize Chen. Carbon-Aware EV Charging. In IEEE SmartGridComm, 2022."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2020.07.017"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"crossref","first-page":"104708","DOI":"10.1016\/j.scs.2023.104708","article-title":"Smart Charging Strategy for Electric Vehicles Based on Marginal Carbon Emission Factors and Time-Of-Use Price","volume":"96","author":"Li Jiale","year":"2023","unstructured":"Jiale Li, Guilin Wang, Xuefei Wang, and Yingkang Du. Smart Charging Strategy for Electric Vehicles Based on Marginal Carbon Emission Factors and Time-Of-Use Price. Sustainable Cities and Society, 96:104708, 2023.","journal-title":"Sustainable Cities and Society"},{"key":"e_1_3_2_1_32_1","volume-title":"ICML","author":"Goswami Mononito","year":"2024","unstructured":"Mononito Goswami, Konrad Szafer, Arjun Choudhry, Yifu Cai, Shuo Li, and Artur Dubrawski. MOMENT: A Family of Open Time-Series Foundation Models. In ICML, 2024."},{"key":"e_1_3_2_1_33_1","volume-title":"Chronos: Learning the Language of Time Series. arXiv preprint arXiv:2403.07815","author":"Ansari Abdul Fatir","year":"2024","unstructured":"Abdul Fatir Ansari et al. Chronos: Learning the Language of Time Series. arXiv preprint arXiv:2403.07815, 2024."},{"key":"e_1_3_2_1_34_1","volume-title":"ACM e-Energy","author":"Maji Diptyaroop","year":"2026","unstructured":"Diptyaroop Maji, Kang Yang, Prashant Shenoy, Ramesh K. Sitaraman, and Mani Srivastava. CarbonX: An Open-Source Tool for Computational Decarbonization Using Time Series Foundation Models. In ACM e-Energy, 2026."},{"key":"e_1_3_2_1_35_1","volume-title":"Benchmarking Spatiotemporal Reasoning in LLMs and Reasoning Models: Capabilities and Challenges. arXiv preprint arXiv:2505.11618","author":"Quan Pengrui","year":"2025","unstructured":"Pengrui Quan, Brian Wang, Kang Yang, Liying Han, and Mani Srivastava. Benchmarking Spatiotemporal Reasoning in LLMs and Reasoning Models: Capabilities and Challenges. arXiv preprint arXiv:2505.11618, 2025."},{"key":"e_1_3_2_1_36_1","volume-title":"Sundial: A Family of Highly Capable Time Series Foundation Models. arXiv preprint arXiv:2502.00816","author":"Liu Yong","year":"2025","unstructured":"Yong Liu, Guo Qin, Zhiyuan Shi, Zhi Chen, Caiyin Yang, Xiangdong Huang, Jianmin Wang, and Mingsheng Long. Sundial: A Family of Highly Capable Time Series Foundation Models. arXiv preprint arXiv:2502.00816, 2025."},{"key":"e_1_3_2_1_37_1","volume-title":"Jetson - Embedded AI Computing Platform. https:\/\/developer.nvidia.com\/embedded-computing","author":"NVIDIA.","year":"2026","unstructured":"NVIDIA. Jetson - Embedded AI Computing Platform. https:\/\/developer.nvidia.com\/embedded-computing, 2026. Accessed: 2026-03-16."},{"key":"e_1_3_2_1_38_1","volume-title":"December 10","author":"Temam Olivier","year":"2019","unstructured":"Olivier Temam, Harshit Khaitan, Ravi Narayanaswami, and Dong Hyuk Woo. Neural Network Accelerator with Parameters Resident on Chip, December 10 2019. Patent# US20190050717A1."},{"key":"e_1_3_2_1_39_1","volume-title":"IEEE INFOCOM","author":"Tan Tianxiang","year":"2022","unstructured":"Tianxiang Tan and Guohong Cao. Deep Learning on Mobile Devices through Neural Processing Units and Edge Computing. In IEEE INFOCOM, 2022."},{"key":"e_1_3_2_1_40_1","volume-title":"SEC","author":"Dong Qifei","year":"2025","unstructured":"Qifei Dong, Jingao Xu, Padmanabhan Pillai, and Mahadev Satyanarayanan. Does Accurate Real-Time AI Need Edge Offload? In SEC, 2025."},{"key":"e_1_3_2_1_41_1","volume-title":"Battery Pack Prices Drop. https:\/\/www.batterytechonline.com\/trends\/battery-pack-prices-drop-8-to-record-108kwh-despite-rising-lithium-and-cobalt-costs-in-2025","author":"Hertz Jake","year":"2025","unstructured":"Jake Hertz. Battery Pack Prices Drop. https:\/\/www.batterytechonline.com\/trends\/battery-pack-prices-drop-8-to-record-108kwh-despite-rising-lithium-and-cobalt-costs-in-2025, 2025. [Online]."},{"key":"e_1_3_2_1_42_1","volume-title":"Tajana Simunic Rosing. Accuracy-Resource Tradeoff for Edge Devices in Internet of Things. In IEEE PerCom Workshops","author":"Mousavi Nima","year":"2017","unstructured":"Nima Mousavi, Baris Aksanli, Alper Sinan Akyurek, and Tajana Simunic Rosing. Accuracy-Resource Tradeoff for Edge Devices in Internet of Things. In IEEE PerCom Workshops, 2017."},{"issue":"1","key":"e_1_3_2_1_43_1","doi-asserted-by":"crossref","first-page":"10301","DOI":"10.1038\/s41467-024-54634-y","article-title":"Carbon Footprint Distributions of Lithium-Ion Batteries and Their Materials","volume":"15","author":"Peiseler Leopold","year":"2024","unstructured":"Leopold Peiseler, Vanessa Schenker, Karin Schatzmann, Stephan Pfister, Vanessa Wood, and Tobias Schmidt. Carbon Footprint Distributions of Lithium-Ion Batteries and Their Materials. Nature Communications, 15(1):10301, 2024.","journal-title":"Nature Communications"},{"key":"e_1_3_2_1_44_1","volume-title":"ACM MobiSys","author":"Chen Xuesi","year":"2026","unstructured":"Xuesi Chen, Ilan Mandel, Eren Yildiz, Josiah Hester, and Udit Gupta. A Greener Edge: A Framework on Carbon-Aware Edge ML System Design. In ACM MobiSys, 2026."},{"key":"e_1_3_2_1_45_1","volume-title":"HPDC","author":"Wu Li","year":"2025","unstructured":"Li Wu, Walid A. Hanafy, Abel Souza, Khai Nguyen, Jan Harkes, David Irwin, Mahadev Satyanarayanan, and Prashant Shenoy. CarbonEdge: Leveraging Mesoscale Spatial Carbon-Intensity Variations for Low Carbon Edge Computing. In HPDC, 2025."},{"key":"e_1_3_2_1_46_1","volume-title":"ACM Journal on Computing and Sustainable Societies","author":"Bovornkeeratiroj Phuthipong","year":"2025","unstructured":"Phuthipong Bovornkeeratiroj, Walid A. Hanafy, David Irwin, and Prashant Shenoy. GreenThrift: Optimizing Carbon and Cost for Flexible Residential Loads. ACM Journal on Computing and Sustainable Societies, 2025."},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3626788"},{"key":"e_1_3_2_1_48_1","volume-title":"ECCV","author":"Lin Tsung-Yi","year":"2014","unstructured":"Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll\u00e1r, and C Lawrence Zitnick. Microsoft COCO: Common Objects in Context. In ECCV, 2014."},{"issue":"2","key":"e_1_3_2_1_49_1","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/MIE.2013.2250351","article-title":"Battery Management System","volume":"7","author":"Rahimi-Eichi Habiballah","year":"2013","unstructured":"Habiballah Rahimi-Eichi, Unnati Ojha, Federico Baronti, and Mo-Yuen Chow. Battery Management System: An Overview of Its Application in the Smart Grid and Electric Vehicles. IEEE Industrial Electronics Magazine, 7(2):4\u201316, 2013.","journal-title":"IEEE Industrial Electronics Magazine"},{"issue":"35","key":"e_1_3_2_1_50_1","first-page":"223","article-title":"Law of a Lead-Acid Battery Simulated by a Mathematical Model","volume":"25","author":"Cugnet Mik\u00e4el G","year":"2010","unstructured":"Mik\u00e4el G Cugnet, Matthieu Dubarry, and Bor Yann Liaw. Peukert's Law of a Lead-Acid Battery Simulated by a Mathematical Model. Electrochemical Society Transactions, 25(35):223\u2013233, 2010.","journal-title":"Electrochemical Society Transactions"},{"key":"e_1_3_2_1_51_1","volume-title":"Spectral Predictability as a Fast Reliability Indicator for Time Series Forecasting Model Selection. arXiv preprint arXiv:2511.08884","author":"Wang Oliver","year":"2025","unstructured":"Oliver Wang, Pengrui Quan, Kang Yang, and Mani Srivastava. Spectral Predictability as a Fast Reliability Indicator for Time Series Forecasting Model Selection. arXiv preprint arXiv:2511.08884, 2025."},{"key":"e_1_3_2_1_52_1","volume-title":"iPhone Batteries Compared: Capacity, mAh and Watt Hours for Every iPhone. https:\/\/www.macworld.com\/article\/678413\/iphone-battery-capacities-compared-all-iphones-battery-life-in-mah-and-wh.html","author":"Jary Simon","year":"2026","unstructured":"Simon Jary. iPhone Batteries Compared: Capacity, mAh and Watt Hours for Every iPhone. https:\/\/www.macworld.com\/article\/678413\/iphone-battery-capacities-compared-all-iphones-battery-life-in-mah-and-wh.html, 2026. [Online]."},{"key":"e_1_3_2_1_53_1","volume-title":"ICSOC","author":"Alqahtani Daghash K","year":"2024","unstructured":"Daghash K Alqahtani, Muhammad Aamir Cheema, and Adel N Toosi. Benchmarking Deep Learning Models for Object Detection on Edge Computing Devices. In ICSOC, 2024."}],"event":{"name":"ISLPED '26: ACM\/IEEE International Symposium on Low Power Electronics and Design","location":"Evanston IL USA","acronym":"ISLPED '26","sponsor":["SIGDA ACM Special Interest Group on Design Automation"]},"container-title":["Proceedings of the ACM\/IEEE International Symposium on Low Power Electronics and Design"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3816440.3818532","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T19:24:51Z","timestamp":1786389891000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3816440.3818532"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,5]]},"references-count":53,"alternative-id":["10.1145\/3816440.3818532","10.1145\/3816440"],"URL":"https:\/\/doi.org\/10.1145\/3816440.3818532","relation":{},"subject":[],"published":{"date-parts":[[2026,8,5]]},"assertion":[{"value":"2026-08-10","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}