{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T23:36:00Z","timestamp":1781912160606,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":60,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T00:00:00Z","timestamp":1746489600000},"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":[[2025,5,6]]},"DOI":"10.1145\/3715014.3722067","type":"proceedings-article","created":{"date-parts":[[2025,5,4]],"date-time":"2025-05-04T23:39:01Z","timestamp":1746401941000},"page":"158-171","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["LightLLM: A Versatile Large Language Model for Predictive Light Sensing"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0336-4144","authenticated-orcid":false,"given":"Jiawei","family":"Hu","sequence":"first","affiliation":[{"name":"UNSW, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6047-4158","authenticated-orcid":false,"given":"Hong","family":"Jia","sequence":"additional","affiliation":[{"name":"University of Melbourne, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3417-8590","authenticated-orcid":false,"given":"Mahbub","family":"Hassan","sequence":"additional","affiliation":[{"name":"University of New South Wales, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4149-839X","authenticated-orcid":false,"given":"Lina","family":"Yao","sequence":"additional","affiliation":[{"name":"CSIRO, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9082-3243","authenticated-orcid":false,"given":"Brano","family":"Kusy","sequence":"additional","affiliation":[{"name":"CSIRO, Brisbane, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4076-1811","authenticated-orcid":false,"given":"Wen","family":"Hu","sequence":"additional","affiliation":[{"name":"UNSW, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,5,6]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"2023. Original Samsung Smart TV Remote (Solar Cell Remote Control - BN59-01385B Genuine). https:\/\/remotecontrolwarehouse.com.au\/products\/."},{"key":"e_1_3_2_1_2_1","volume-title":"Large language models are few-shot clinical information extractors. arXiv preprint arXiv:2205.12689","author":"Agrawal Monica","year":"2022","unstructured":"Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, and David Sontag. 2022. Large language models are few-shot clinical information extractors. arXiv preprint arXiv:2205.12689 (2022)."},{"key":"e_1_3_2_1_3_1","unstructured":"Mistral AI. 2024. Mistral. https:\/\/mistral.ai\/."},{"key":"e_1_3_2_1_4_1","unstructured":"ams OSRAM. 2022. AS7265x Smart Spectral Sensor. https:\/\/ams.com\/en\/as7265x."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2993422.2993577"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1080\/15487733.2017.1394054"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.3390\/polym12061338"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-022-01435-x"},{"key":"e_1_3_2_1_9_1","volume-title":"Fundamentals of renewable energy processes","author":"Da Rosa Aldo Vieira","unstructured":"Aldo Vieira Da Rosa and Juan Carlos Ordonez. 2021. Fundamentals of renewable energy processes. Academic Press."},{"key":"e_1_3_2_1_10_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_1_11_1","volume-title":"Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, et al.","author":"Driess Danny","year":"2023","unstructured":"Danny Driess, Fei Xia, Mehdi SM Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, et al. 2023. Palm-e: An embodied multimodal language model. arXiv preprint arXiv:2303.03378 (2023)."},{"key":"e_1_3_2_1_12_1","volume-title":"Saudi Arabia. Applied energy 87, 2","author":"El-Sebaii AA","year":"2010","unstructured":"AA El-Sebaii, FS Al-Hazmi, AA Al-Ghamdi, and Saud Jameel Yaghmour. 2010. Global, direct and diffuse solar radiation on horizontal and tilted surfaces in Jeddah, Saudi Arabia. Applied energy 87, 2 (2010), 568--576."},{"key":"e_1_3_2_1_13_1","volume-title":"Fate-llm: A industrial grade federated learning framework for large language models. arXiv preprint arXiv:2310.10049","author":"Fan Tao","year":"2023","unstructured":"Tao Fan, Yan Kang, Guoqiang Ma, Weijing Chen, Wenbin Wei, Lixin Fan, and Qiang Yang. 2023. Fate-llm: A industrial grade federated learning framework for large language models. arXiv preprint arXiv:2310.10049 (2023)."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-statistics-062713-085831"},{"key":"e_1_3_2_1_15_1","unstructured":"Ian Goodfellow. 2016. Deep learning."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"e_1_3_2_1_17_1","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 11474--11484","author":"Guen Vincent Le","year":"2020","unstructured":"Vincent Le Guen and Nicolas Thome. 2020. Disentangling physical dynamics from unknown factors for unsupervised video prediction. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. 11474--11484."},{"key":"e_1_3_2_1_18_1","volume-title":"Lora: Low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685","author":"Hu Edward J","year":"2021","unstructured":"Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021. Lora: Low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685 (2021)."},{"key":"e_1_3_2_1_19_1","first-page":"1","article-title":"Iris: Passive Visible Light Positioning Using Light Spectral Information","volume":"7","author":"Hu Jiawei","year":"2023","unstructured":"Jiawei Hu, Yanxiang Wang, Hong Jia, Wen Hu, Mahbub Hassan, Brano Kusy, Ashraf Uddin, and Moustafa Youssef. 2023. Iris: Passive Visible Light Positioning Using Light Spectral Information. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 7, 3 (2023), 1--27.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"e_1_3_2_1_20_1","volume-title":"LiDARSpectra: Synthetic Indoor Spectral Mapping with Low-cost LiDARs. In 2024 23rd ACM\/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE, 75--87","author":"Hu Jiawei","year":"2024","unstructured":"Jiawei Hu, Yanxiang Wang, Hong Jia, Cheng Jiang, Mahbub Hassan, Brano Kusy, and Wen Hu. 2024. LiDARSpectra: Synthetic Indoor Spectral Mapping with Low-cost LiDARs. In 2024 23rd ACM\/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE, 75--87."},{"key":"e_1_3_2_1_21_1","volume-title":"Hugo TC Pedro, and Carlos FM Coimbra","author":"Inman Rich H","year":"2013","unstructured":"Rich H Inman, Hugo TC Pedro, and Carlos FM Coimbra. 2013. Solar forecasting methods for renewable energy integration. Progress in energy and combustion science 39, 6 (2013), 535--576."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.solener.2017.08.077"},{"key":"e_1_3_2_1_23_1","volume-title":"HARGPT: Are LLMs Zero-Shot Human Activity Recognizers? arXiv preprint arXiv:2403.02727","author":"Ji Sijie","year":"2024","unstructured":"Sijie Ji, Xinzhe Zheng, and Chenshu Wu. 2024. HARGPT: Are LLMs Zero-Shot Human Activity Recognizers? arXiv preprint arXiv:2403.02727 (2024)."},{"key":"e_1_3_2_1_24_1","volume-title":"Time-llm: Time series forecasting by reprogramming large language models. arXiv preprint arXiv:2310.01728","author":"Jin Ming","year":"2023","unstructured":"Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Y Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, et al. 2023. Time-llm: Time series forecasting by reprogramming large language models. arXiv preprint arXiv:2310.01728 (2023)."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2019.2944178"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.113"},{"key":"e_1_3_2_1_27_1","volume-title":"Prefix-tuning: Optimizing continuous prompts for generation. arXiv preprint arXiv:2101.00190","author":"Li Xiang Lisa","year":"2021","unstructured":"Xiang Lisa Li and Percy Liang. 2021. Prefix-tuning: Optimizing continuous prompts for generation. arXiv preprint arXiv:2101.00190 (2021)."},{"key":"e_1_3_2_1_28_1","volume-title":"A survey of convolutional neural networks: analysis, applications, and prospects","author":"Li Zewen","year":"2021","unstructured":"Zewen Li, Fan Liu, Wenjie Yang, Shouheng Peng, and Jun Zhou. 2021. A survey of convolutional neural networks: analysis, applications, and prospects. IEEE transactions on neural networks and learning systems 33, 12 (2021), 6999--7019."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3560815"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3643832.3661872"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3300061.3300129"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376368"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.solener.2023.03.043"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.adapen.2024.100172"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.solener.2021.05.056"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0030-4018(98)00192-8"},{"key":"e_1_3_2_1_38_1","volume-title":"Pytorch: An imperative style, high-performance deep learning library. Advances in neural information processing systems 32","author":"Paszke Adam","year":"2019","unstructured":"Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al. 2019. Pytorch: An imperative style, high-performance deep learning library. Advances in neural information processing systems 32 (2019)."},{"key":"e_1_3_2_1_39_1","volume-title":"Dataset shift in machine learning","author":"Qui\u00f1onero-Candela Joaquin","unstructured":"Joaquin Qui\u00f1onero-Candela, Masashi Sugiyama, Anton Schwaighofer, and Neil D Lawrence. 2022. Dataset shift in machine learning. Mit Press."},{"key":"e_1_3_2_1_40_1","volume-title":"International conference on machine learning. PMLR, 8748--8763","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021. Learning transferable visual models from natural language supervision. In International conference on machine learning. PMLR, 8748--8763."},{"key":"e_1_3_2_1_41_1","unstructured":"Machel Reid Nikolay Savinov Denis Teplyashin Dmitry Lepikhin Timothy Lillicrap Jean-baptiste Alayrac Radu Soricut Angeliki Lazaridou Orhan Firat Julian Schrittwieser et al. 2024. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context. arXiv preprint arXiv:2403.05530 (2024)."},{"key":"e_1_3_2_1_42_1","volume-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting. Advances in neural information processing systems 28","author":"Shi Xingjian","year":"2015","unstructured":"Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, and Wang-chun Woo. 2015. Convolutional LSTM network: A machine learning approach for precipitation nowcasting. Advances in neural information processing systems 28 (2015)."},{"key":"e_1_3_2_1_43_1","unstructured":"Karan Singhal Tao Tu Juraj Gottweis Rory Sayres Ellery Wulczyn Le Hou Kevin Clark Stephen Pfohl Heather Cole-Lewis Darlene Neal et al. 2023. Towards expert-level medical question answering with large language models. arXiv preprint arXiv:2305.09617 (2023)."},{"key":"e_1_3_2_1_44_1","volume-title":"Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971","author":"Touvron Hugo","year":"2023","unstructured":"Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timoth\u00e9e Lacroix, Baptiste Rozi\u00e8re, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023. Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971 (2023)."},{"key":"e_1_3_2_1_45_1","volume-title":"Attention is all you need. Advances in Neural Information Processing Systems","author":"Vaswani A","year":"2017","unstructured":"A Vaswani. 2017. Attention is all you need. Advances in Neural Information Processing Systems (2017)."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3610890"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2016.10.079"},{"key":"e_1_3_2_1_48_1","volume-title":"Denny Zhou, et al.","author":"Wei Jason","year":"2022","unstructured":"Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022. Chain-of-thought prompting elicits reasoning in large language models. Advances in neural information processing systems 35 (2022), 24824--24837."},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-016-0043-6"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3666025.3699349"},{"key":"e_1_3_2_1_51_1","volume-title":"Organic---inorganic hybrid solar cells: A comparative review. Solar energy materials and solar cells 107","author":"Wright Matthew","year":"2012","unstructured":"Matthew Wright and Ashraf Uddin. 2012. Organic---inorganic hybrid solar cells: A comparative review. Solar energy materials and solar cells 107 (2012), 87--111."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3651890.3672268"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"e_1_3_2_1_54_1","first-page":"1","article-title":"Mental-llm: Leveraging large language models for mental health prediction via online text data","volume":"8","author":"Xu Xuhai","year":"2024","unstructured":"Xuhai Xu, Bingsheng Yao, Yuanzhe Dong, Saadia Gabriel, Hong Yu, James Hendler, Marzyeh Ghassemi, Anind K Dey, and Dakuo Wang. 2024. Mental-llm: Leveraging large language models for mental health prediction via online text data. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 8, 1 (2024), 1--32.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"e_1_3_2_1_55_1","volume-title":"Are You Being Tracked? Discover the Power of Zero-Shot Trajectory Tracing with LLMs! arXiv preprint arXiv:2403.06201","author":"Yang Huanqi","year":"2024","unstructured":"Huanqi Yang, Sijie Ji, Rucheng Wu, and Weitao Xu. 2024. Are You Being Tracked? Discover the Power of Zero-Shot Trajectory Tracing with LLMs! arXiv preprint arXiv:2403.06201 (2024)."},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2010.12.028"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3117811.3117821"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.solener.2018.10.024"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.7000"},{"key":"e_1_3_2_1_60_1","volume-title":"Deep learning in remote sensing: A comprehensive review and list of resources","author":"Zhu Xiao Xiang","year":"2017","unstructured":"Xiao Xiang Zhu, Devis Tuia, Lichao Mou, Gui-Song Xia, Liangpei Zhang, Feng Xu, and Friedrich Fraundorfer. 2017. Deep learning in remote sensing: A comprehensive review and list of resources. IEEE geoscience and remote sensing magazine 5, 4 (2017), 8--36."},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2020.3004555"}],"event":{"name":"SenSys '25: 23rd ACM Conference on Embedded Networked Sensor Systems","location":"UC Irvine Student Center. Irvine CA USA","acronym":"SenSys '25","sponsor":["SIGARCH ACM Special Interest Group on Computer Architecture","SIGMETRICS ACM Special Interest Group on Measurement and Evaluation","SIGOPS ACM Special Interest Group on Operating Systems","SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing","SIGBED ACM Special Interest Group on Embedded Systems"]},"container-title":["Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3715014.3722067","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:56:51Z","timestamp":1750298211000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3715014.3722067"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,6]]},"references-count":60,"alternative-id":["10.1145\/3715014.3722067","10.1145\/3715014"],"URL":"https:\/\/doi.org\/10.1145\/3715014.3722067","relation":{},"subject":[],"published":{"date-parts":[[2025,5,6]]},"assertion":[{"value":"2025-05-06","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}