{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T17:14:14Z","timestamp":1740158054755,"version":"3.37.3"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2021,8,16]],"date-time":"2021-08-16T00:00:00Z","timestamp":1629072000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,8,16]],"date-time":"2021-08-16T00:00:00Z","timestamp":1629072000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1007\/s12652-021-03432-1","type":"journal-article","created":{"date-parts":[[2021,8,16]],"date-time":"2021-08-16T17:04:37Z","timestamp":1629133477000},"page":"3019-3040","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Designing adaptive passive personal mobile sensing methods using reinforcement learning framework"],"prefix":"10.1007","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0136-9857","authenticated-orcid":false,"given":"Lihua","family":"Cai","sequence":"first","affiliation":[]},{"given":"Laura E.","family":"Barnes","sequence":"additional","affiliation":[]},{"given":"Mehdi","family":"Boukhechba","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,8,16]]},"reference":[{"key":"3432_CR1","doi-asserted-by":"crossref","unstructured":"Balan RK, Lee Y, Wee TK, Misra A (2014) The challenge of continuous mobile context sensing. In: 2014 sixth international conference on communication systems and networks (COMSNETS). IEEE, pp 1\u20138","DOI":"10.1109\/COMSNETS.2014.6734869"},{"key":"3432_CR2","unstructured":"Ben AF, Phillips A, Henderson T (2009) Less is more: energy-efficient mobile sensing with senseless. In: Proceedings of the 1st ACM workshop on networking, systems, and applications for mobile handhelds. ACM, pp 61\u201362"},{"issue":"4","key":"3432_CR3","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1007\/s13218-015-0356-1","volume":"29","author":"W B\u00f6hmer","year":"2015","unstructured":"B\u00f6hmer W, Springenberg JT, Boedecker J, Riedmiller M, Obermayer K (2015) Autonomous learning of state representations for control: an emerging field aims to autonomously learn state representations for reinforcement learning agents from their real-world sensor observations. KI-K\u00fcnstl Intell 29(4):353\u2013362","journal-title":"KI-K\u00fcnstl Intell"},{"key":"3432_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2016\/6156914","volume":"2016","author":"B Mehdi","year":"2016","unstructured":"Mehdi B, Abdenour B, Bruno B, Charles G-V, Sylvain G (2016a) Energy optimization for outdoor activity recognition. J Sens 2016:1\u201315. https:\/\/doi.org\/10.1155\/2016\/6156914","journal-title":"J Sens"},{"key":"3432_CR5","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.procs.2016.08.008","volume":"94","author":"M Boukhechba","year":"2016","unstructured":"Boukhechba M, Bouzouane A, Gaboury S, Gouin-Vallerand C, Giroux S, Bouchard B (2016b) Hybrid battery-friendly mobile solution for extracting users\u2019 visited places. Proc Comput Sci 94:25\u201332. https:\/\/doi.org\/10.1016\/j.procs.2016.08.008","journal-title":"Proc Comput Sci"},{"key":"3432_CR6","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1016\/j.smhl.2018.07.005","volume":"9\u201310","author":"DAR Boukhechba","year":"2018","unstructured":"Boukhechba DAR, Fua K, Chow PI, Teachman BA, Barnes LE (2018a) DemonicSalmon: monitoring mental health and social interactions of college students using smartphones. Smart Health 9\u201310:192\u2013203. https:\/\/doi.org\/10.1016\/j.smhl.2018.07.005","journal-title":"Smart Health"},{"key":"3432_CR7","doi-asserted-by":"publisher","unstructured":"Boukhechba M, Daros A, Chow P, Fua K, Teachman B, Barnes L (2018b) Demonicsalmon. https:\/\/doi.org\/10.17605\/OSF.IO\/WDUK6","DOI":"10.17605\/OSF.IO\/WDUK6"},{"key":"3432_CR8","doi-asserted-by":"crossref","unstructured":"Cai L, Boukhechba M, Kaur N, Wu C, Barnes LE, Gerber MS (2019) Adaptive passive mobile sensing using reinforcement learning. In: 2019 IEEE 20th international symposium on \u201da world of wireless, mobile and multimedia networks\u201d (WoWMoM). IEEE, pp 1\u20136","DOI":"10.1109\/WoWMoM.2019.8792967"},{"key":"3432_CR9","doi-asserted-by":"crossref","unstructured":"Canzian L, Musolesi M (2015) Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis. In: Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing. ACM, pp 1293\u20131304","DOI":"10.1145\/2750858.2805845"},{"issue":"3","key":"3432_CR10","doi-asserted-by":"publisher","first-page":"538937","DOI":"10.1155\/2013\/538937","volume":"9","author":"G Cardone","year":"2013","unstructured":"Cardone G, Cirri A, Corradi A, Foschini L, Maio D (2013) Msf: an efficient mobile phone sensing framework. Int J Distrib Sens Netw 9(3):538937","journal-title":"Int J Distrib Sens Netw"},{"key":"3432_CR11","doi-asserted-by":"crossref","unstructured":"Constandache I, Gaonkar S, Sayler M, Choudhury RR, Cox L (2009) Enloc: energy-efficient localization for mobile phones. In: IEEE INFOCOM 2009. IEEE, pp 2716\u20132720","DOI":"10.1109\/INFCOM.2009.5062218"},{"issue":"12","key":"3432_CR12","doi-asserted-by":"publisher","first-page":"1182","DOI":"10.1002\/da.22970","volume":"36","author":"KE Daniel","year":"2019","unstructured":"Daniel KE, Baee S, Boukhechba M, Barnes LE, Teachman BA (2019) Do I really feel better? Effectiveness of emotion regulation strategies depends on the measure and social anxiety. Depr Anxiety 36(12):1182\u20131190","journal-title":"Depr Anxiety"},{"issue":"4","key":"3432_CR13","doi-asserted-by":"publisher","first-page":"743","DOI":"10.1080\/02699931.2019.1681364","volume":"34","author":"AR Daros","year":"2020","unstructured":"Daros AR, Daniel KE, Boukhechba M, Chow PI, Barnes LE, Teachman BA (2020) Relationships between trait emotion dysregulation and emotional experiences in daily life: an experience sampling study. Cogn Emot 34(4):743\u2013755","journal-title":"Cogn Emot"},{"issue":"4","key":"3432_CR14","doi-asserted-by":"publisher","first-page":"274","DOI":"10.4103\/0974-7788.76794","volume":"1","author":"MK Goel","year":"2010","unstructured":"Goel MK, Khanna P, Kishore J (2010) Understanding survival analysis: Kaplan-Meier estimate. Int J Ayurveda Res 1(4):274","journal-title":"Int J Ayurveda Res"},{"key":"3432_CR15","doi-asserted-by":"crossref","unstructured":"Kang JH, Welbourne W, Stewart B, Borriello G (2004) Extracting places from traces of locations. In: Proceedings of the 2nd ACM international workshop on Wireless mobile applications and services on WLAN hotspots. ACM, pp 110\u2013118","DOI":"10.1145\/1024733.1024748"},{"key":"3432_CR16","doi-asserted-by":"crossref","unstructured":"Kansal A, Saponas S, Brush AJ, McKinley KS, Mytkowicz T, Ziola R (2013) The latency, accuracy, and battery (lab) abstraction: programmer productivity and energy efficiency for continuous mobile context sensing. In: ACM SIGPLAN Notices, vol 48. ACM, pp 661\u2013676","DOI":"10.1145\/2544173.2509541"},{"key":"3432_CR17","doi-asserted-by":"crossref","unstructured":"Khan A, Hammerla N, Mellor S, Pl\u00f6tz T (2016) Optimising sampling rates for accelerometer-based human activity recognition. Pattern Recognit Lett","DOI":"10.1016\/j.patrec.2016.01.001"},{"key":"3432_CR18","doi-asserted-by":"crossref","unstructured":"Kim K-H, Min AW, Gupta D, Mohapatra P, Singh JP (2011) Improving energy efficiency of Wi-Fi sensing on smartphones. In: 2011 proceedings IEEE INFOCOM. IEEE, pp 2930\u20132938","DOI":"10.1109\/INFCOM.2011.5935133"},{"key":"3432_CR19","doi-asserted-by":"crossref","unstructured":"Krause A, Ihmig M, Rankin E, Leong D, Gupta S, Siewiorek D, Smailagic A, Deisher M, Sengupta U (2005) Trading off prediction accuracy and power consumption for context-aware wearable computing. In: Wearable computers, 2005. Proceedings. Ninth IEEE international symposium on. IEEE, pp 20\u201326","DOI":"10.1109\/ISWC.2005.52"},{"key":"3432_CR20","doi-asserted-by":"crossref","unstructured":"Lane ND, Bhattacharya S, Georgiev P, Forlivesi C, Jiao L, Qendro L, Kawsar F (2016) Deepx: a software accelerator for low-power deep learning inference on mobile devices. In: Proceedings of the 15th international conference on information processing in sensor networks. IEEE Press, p 23","DOI":"10.1109\/IPSN.2016.7460664"},{"issue":"9","key":"3432_CR21","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1109\/MCOM.2010.5560598","volume":"48","author":"ND Lane","year":"2010","unstructured":"Lane ND, Miluzzo E, Hong L, Peebles D, Choudhury T, Campbell AT (2010) A survey of mobile phone sensing. IEEE Commun Mag 48(9):140\u2013150","journal-title":"IEEE Commun Mag"},{"issue":"2","key":"3432_CR22","first-page":"35","volume":"3","author":"X Li","year":"2012","unstructured":"Li X, Cao H, Chen E, Tian J (2012) Learning to infer the status of heavy-duty sensors for energy-efficient context-sensing. ACM Trans Intell Syst Technol (TIST) 3(2):35","journal-title":"ACM Trans Intell Syst Technol (TIST)"},{"key":"3432_CR23","doi-asserted-by":"crossref","unstructured":"Lin K, Kansal A, Lymberopoulos D, Zhao F (2010) Energy-accuracy trade-off for continuous mobile device location. In: Proceedings of the 8th international conference on mobile systems, applications, and services. ACM, pp 285\u2013298","DOI":"10.1145\/1814433.1814462"},{"key":"3432_CR24","doi-asserted-by":"crossref","unstructured":"Lu H, Brush AJB, Priyantha B, Karlson AK, Liu J (2011) Speakersense: energy efficient unobtrusive speaker identification on mobile phones. In: International conference on pervasive computing. Springer, pp 188\u2013205","DOI":"10.1007\/978-3-642-21726-5_12"},{"key":"3432_CR25","doi-asserted-by":"crossref","unstructured":"Lu H, Yang J, Liu Z, Lane ND, Choudhury Tanzeem, Campbell Andrew T (2010) The jigsaw continuous sensing engine for mobile phone applications. In: Proceedings of the 8th ACM conference on embedded networked sensor systems, pp 71\u201384. ACM","DOI":"10.1145\/1869983.1869992"},{"issue":"12","key":"3432_CR26","doi-asserted-by":"publisher","first-page":"17292","DOI":"10.3390\/s131217292","volume":"13","author":"E Macias","year":"2013","unstructured":"Macias E, Suarez A, Lloret J (2013) Mobile sensing systems. Sensors 13(12):17292\u201317321","journal-title":"Sensors"},{"issue":"4","key":"3432_CR27","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1016\/S0005-7967(97)10031-6","volume":"36","author":"RP Mattick","year":"1998","unstructured":"Mattick RP, Clarke JC (1998) Development and validation of measures of social phobia scrutiny fear and social interaction anxiety. Behav Res Ther 36(4):455\u2013470","journal-title":"Behav Res Ther"},{"key":"3432_CR28","doi-asserted-by":"crossref","unstructured":"Mehrotra A, Pejovic V, Musolesi M (2014) Sensocial: a middleware for integrating online social networks and mobile sensing data streams. In: Proceedings of the 15th international middleware conference. ACM, pp 205\u2013216","DOI":"10.1145\/2663165.2663331"},{"key":"3432_CR29","doi-asserted-by":"crossref","unstructured":"Min J-K, Doryab A, Wiese J, Amini S, Zimmerman J, Hong JI (2014) Toss\u2019n\u2019turn: smartphone as sleep and sleep quality detector. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 477\u2013486","DOI":"10.1145\/2556288.2557220"},{"key":"3432_CR30","doi-asserted-by":"crossref","unstructured":"Oshin TO, Poslad S, Ma A (2012) Improving the energy-efficiency of gps based location sensing smartphone applications. In: 2012 IEEE 11th international conference on trust, security and privacy in computing and communications. IEEE, pp 1698\u20131705","DOI":"10.1109\/TrustCom.2012.184"},{"key":"3432_CR31","doi-asserted-by":"crossref","unstructured":"Paek J, Kim J, Govindan R (2010) Energy-efficient rate-adaptive gps-based positioning for smartphones. In: Proceedings of the 8th international conference on mobile systems, applications, and services. ACM, pp 299\u2013314","DOI":"10.1145\/1814433.1814463"},{"issue":"1","key":"3432_CR32","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1007\/s11036-012-0422-y","volume":"18","author":"W Pang","year":"2013","unstructured":"Pang W, Zhu J, Zhang JY (2013) Mobisens: a versatile mobile sensing platform for real-world applications. Mob Netw Appl 18(1):60\u201380","journal-title":"Mob Netw Appl"},{"issue":"4","key":"3432_CR33","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1109\/TCSS.2016.2515844","volume":"2","author":"C Perera","year":"2015","unstructured":"Perera C, Talagala DS, Liu CH, Estrella JC (2015) Energy-efficient location and activity-aware on-demand mobile distributed sensing platform for sensing as a service in iot clouds. IEEE Trans Comput Soc Syst 2(4):171\u2013181","journal-title":"IEEE Trans Comput Soc Syst"},{"key":"3432_CR34","unstructured":"Pl\u00f6tz T, Hammerla NY, Olivier PL (2011) Feature learning for activity recognition in ubiquitous computing. In: Twenty-second international joint conference on artificial intelligence"},{"issue":"3","key":"3432_CR35","doi-asserted-by":"publisher","first-page":"871","DOI":"10.1109\/TBME.2008.2006190","volume":"56","author":"SJ Preece","year":"2008","unstructured":"Preece SJ, Goulermas JY, Kenney LPJ, Howard D (2008) A comparison of feature extraction methods for the classification of dynamic activities from accelerometer data. IEEE Trans Biomed Eng 56(3):871\u2013879","journal-title":"IEEE Trans Biomed Eng"},{"key":"3432_CR36","doi-asserted-by":"crossref","unstructured":"Priyantha B, Lymberopoulos D, Liu J (2010) Enabling energy efficient continuous sensing on mobile phones with littlerock. In: Proceedings of the 9th ACM\/IEEE international conference on information processing in sensor networks. ACM, pp 420\u2013421","DOI":"10.1145\/1791212.1791285"},{"key":"3432_CR37","doi-asserted-by":"crossref","unstructured":"Ra M-R, Priyantha B, Kansal A, Liu J (2012) Improving energy efficiency of personal sensing applications with heterogeneous multi-processors. In: Proceedings of the 2012 ACM conference on ubiquitous computing. ACM, pp 1\u201310","DOI":"10.1145\/2370216.2370218"},{"key":"3432_CR38","doi-asserted-by":"crossref","unstructured":"Rachuri KK, Mascolo C, Musolesi M, Rentfrow PJ (2011) Sociablesense: exploring the trade-offs of adaptive sampling and computation offloading for social sensing. In: Proceedings of the 17th annual international conference on mobile computing and networking. ACM, pp 73\u201384","DOI":"10.1145\/2030613.2030623"},{"key":"3432_CR39","unstructured":"Rachuri KK, Musolesi M, Mascolo C (2010) Energy-accuracy trade-offs in querying sensor data for continuous sensing mobile systems. In: Proc. of mobile context-awareness workshop, vol 10"},{"issue":"9","key":"3432_CR40","doi-asserted-by":"publisher","first-page":"22616","DOI":"10.3390\/s150922616","volume":"15","author":"R Rawassizadeh","year":"2015","unstructured":"Rawassizadeh R, Tomitsch M, Nourizadeh M, Momeni E, Peery A, Ulanova L, Pazzani M (2015) Energy-efficient integration of continuous context sensing and prediction into smartwatches. Sensors 15(9):22616\u201322645","journal-title":"Sensors"},{"key":"3432_CR41","doi-asserted-by":"crossref","unstructured":"Sankaran K, Zhu M, Guo XF, Ananda AL, Chan MC, Peh L-S (2014) Using mobile phone barometer for low-power transportation context detection. In: Proceedings of the 12th ACM conference on embedded network sensor systems. ACM, pp 191\u2013205","DOI":"10.1145\/2668332.2668343"},{"issue":"84","key":"3432_CR42","doi-asserted-by":"publisher","first-page":"20130246","DOI":"10.1098\/rsif.2013.0246","volume":"10","author":"CM Schneider","year":"2013","unstructured":"Schneider CM, Belik V, Couronn\u00e9 T, Smoreda Z, Gonz\u00e1lez MC (2013) Unravelling daily human mobility motifs. J R Soc Interface 10(84):20130246","journal-title":"J R Soc Interface"},{"key":"3432_CR43","volume-title":"Reinforcement learning: an introduction","author":"RS Sutton","year":"2018","unstructured":"Sutton RS, Barto AG (2018) Reinforcement learning: an introduction. MIT Press, Cambridge"},{"key":"3432_CR44","unstructured":"Taylor K, Silver L (2019) Smartphone ownership is growing rapidly around the world, but not always equally. Pew Research Center"},{"issue":"6","key":"3432_CR45","first-page":"4","volume":"41","author":"C Twigg","year":"2003","unstructured":"Twigg C (2003) Catmull-rom splines. Computer 41(6):4\u20136","journal-title":"Computer"},{"issue":"12","key":"3432_CR46","doi-asserted-by":"publisher","first-page":"1549","DOI":"10.1109\/TSMC.2015.2418283","volume":"45","author":"L Wang","year":"2015","unstructured":"Wang L, Zhang D, Yan Z, Xiong H, Xie B (2015) effsense: a novel mobile crowd-sensing framework for energy-efficient and cost-effective data uploading. IEEE Trans Syst Man Cybern Syst 45(12):1549\u20131563","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"3432_CR47","doi-asserted-by":"crossref","unstructured":"Wang Y, Krishnamachari B, Zhao Q, Annavaram M (2009a) The tradeoff between energy efficiency and user state estimation accuracy in mobile sensing. In: International conference on mobile computing, applications, and services. Springer, pp 42\u201358","DOI":"10.1007\/978-3-642-12607-9_4"},{"key":"3432_CR48","doi-asserted-by":"crossref","unstructured":"Wang Y, Lin J, Annavaram M, Jacobson QA, Hong J, Krishnamachari B, Sadeh N (2009b) A framework of energy efficient mobile sensing for automatic user state recognition. In: Proceedings of the 7th international conference on mobile systems, applications, and services. ACM, pp 179\u2013192","DOI":"10.1145\/1555816.1555835"},{"key":"3432_CR49","doi-asserted-by":"crossref","unstructured":"Xiong H, Huang Y, Barnes LE, Gerber MS (2019) Sensus: a cross-platform, general-purpose system for mobile crowdsensing in human-subject studies. In: Proceedings of the 2016 ACM international joint conference on pervasive and ubiquitous computing, pp 415\u2013426. ACM","DOI":"10.1145\/2971648.2971711"},{"key":"3432_CR50","doi-asserted-by":"crossref","unstructured":"Yan Z, Subbaraju V, Chakraborty D, Misra A, Aberer K (2012) Energy-efficient continuous activity recognition on mobile phones: an activity-adaptive approach. In: 2012 16th international symposium on wearable computers (ISWC). IEEE, pp 17\u201324","DOI":"10.1109\/ISWC.2012.23"},{"key":"3432_CR51","doi-asserted-by":"crossref","unstructured":"Zhuang Z, Kim K-H, Singh JP (2010) Improving energy efficiency of location sensing on smartphones. In: Proceedings of the 8th international conference on mobile systems, applications, and services. ACM, pp 315\u2013330 (2010)","DOI":"10.1145\/1814433.1814464"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-021-03432-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-021-03432-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-021-03432-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,28]],"date-time":"2023-03-28T12:41:27Z","timestamp":1680007287000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-021-03432-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,16]]},"references-count":51,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["3432"],"URL":"https:\/\/doi.org\/10.1007\/s12652-021-03432-1","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"type":"print","value":"1868-5137"},{"type":"electronic","value":"1868-5145"}],"subject":[],"published":{"date-parts":[[2021,8,16]]},"assertion":[{"value":"29 September 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 August 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 August 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}