{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T10:50:52Z","timestamp":1761648652144,"version":"build-2065373602"},"reference-count":34,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2019,6,12]],"date-time":"2019-06-12T00:00:00Z","timestamp":1560297600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Due to the limited energy budget, great efforts have been made to improve energy efficiency for wireless sensor networks. The advantage of compressed sensing is that it saves energy because of its sparse sampling; however, it suffers inherent shortcomings in relation to timely data acquisition. In contrast, prediction-based approaches are able to offer timely data acquisition, but the overhead of frequent model synchronization and data sampling weakens the gain in the data reduction. The integration of compressed sensing and prediction-based approaches is one promising data acquisition scheme for the suppression of data transmission, as well as timely collection of critical data, but it is challenging to adaptively and effectively conduct appropriate switching between the two aforementioned data gathering modes. Taking into account the characteristics of data gathering modes and monitored data, this research focuses on several key issues, such as integration framework, adaptive deviation tolerance, and adaptive switching mechanism of data gathering modes. In particular, the adaptive deviation tolerance is proposed for improving the flexibility of data acquisition scheme. The adaptive switching mechanism aims at overcoming the drawbacks in the traditional method that fails to effectively react to the phenomena change unless the sampling frequency is sufficiently high. Through experiments, it is demonstrated that the proposed scheme has good flexibility and scalability, and is capable of simultaneously achieving good energy efficiency and high-quality sensing of critical events.<\/jats:p>","DOI":"10.3390\/s19122654","type":"journal-article","created":{"date-parts":[[2019,6,12]],"date-time":"2019-06-12T10:55:19Z","timestamp":1560336919000},"page":"2654","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Adaptive Data Acquisition with Energy Efficiency and Critical-Sensing Guarantee for Wireless Sensor Networks"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4386-2490","authenticated-orcid":false,"given":"Yuan","family":"Rao","sequence":"first","affiliation":[{"name":"School of Information and Computer Sciences, Anhui Agricultural University, Hefei 230036, China"},{"name":"Key Laboratory of Agricultural IoT, Ministry of Agriculture Rural Affairs, Yangling 712100, China"},{"name":"Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing 210003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1404-1626","authenticated-orcid":false,"given":"Gang","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Information and Computer Sciences, Anhui Agricultural University, Hefei 230036, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information and Computer Sciences, Anhui Agricultural University, Hefei 230036, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information and Computer Sciences, Anhui Agricultural University, Hefei 230036, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhaohui","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Information and Computer Sciences, Anhui Agricultural University, Hefei 230036, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruchuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing 210003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.jnca.2015.09.008","article-title":"Applications of wireless sensor networks for urban areas: A survey","volume":"60","author":"Rashid","year":"2016","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2292","DOI":"10.1016\/j.comnet.2008.04.002","article-title":"Wireless sensor network survey","volume":"52","author":"Yick","year":"2008","journal-title":"Comput. Netw."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1007\/s12083-018-0638-0","article-title":"Two-tiered relay node placement for WSN-based home health monitoring system","volume":"12","author":"Li","year":"2019","journal-title":"Peer-to-Peer Netw. Appl."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1016\/j.compag.2018.12.016","article-title":"An analysis of energy efficiency in Wireless Sensor Networks (WSNs) applied in smart agriculture","volume":"156","year":"2019","journal-title":"Comput. Electron. Agric."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/TPC.2016.2632822","article-title":"Patients\u2019 Adoption of WSN-Based Smart Home Healthcare Systems: An Integrated Model of Facilitators and Barriers","volume":"60","author":"Alaiad","year":"2017","journal-title":"IEEE Trans. Prof. Commun."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.jnca.2018.03.001","article-title":"Self-adaptive implicit contention window adjustment mechanism for QoS optimization in wireless sensor networks","volume":"109","author":"Rao","year":"2018","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1016\/j.ins.2015.10.004","article-title":"Data prediction, compression, and recovery in clustered wireless sensor networks for environmental monitoring applications","volume":"329","author":"Wu","year":"2016","journal-title":"Inf. Sci. (NY)"},{"key":"ref_8","unstructured":"Chong, L., Kui, W., and Min, T. (December, January 28). Energy efficient information collection with the ARIMA model in wireless sensor networks. Proceedings of the GLOBECOM\u2014IEEE Global Telecommunications Conference, St. Louis, MO, USA."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"560","DOI":"10.1109\/TMC.2017.2732979","article-title":"Combining Solar Energy Harvesting with Wireless Charging for Hybrid Wireless Sensor Networks","volume":"17","author":"Wang","year":"2017","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_10","first-page":"58","article-title":"A Survey about Prediction-Based Data Reduction in Wireless Sensor Networks","volume":"49","author":"Dias","year":"2016","journal-title":"ACM Comput. Surv."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1145\/2528948","article-title":"Compression in wireless sensor networks: A survey and comparative evaluation","volume":"10","author":"Razzaque","year":"2013","journal-title":"ACM Trans. Sens. Netw."},{"key":"ref_12","first-page":"3261","article-title":"Compressed sensing based data gathering in wireless sensor networks: A survey","volume":"37","author":"Qiao","year":"2017","journal-title":"J. Comput. Appl."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"10221","DOI":"10.3390\/s150510221","article-title":"A data acquisition protocol for a reactive wireless sensor network monitoring application","volume":"15","author":"Aderohunmu","year":"2015","journal-title":"Sensors"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.pmcj.2015.02.002","article-title":"Adaptive compressive sensing based sample scheduling mechanism for wireless sensor networks","volume":"22","author":"Hao","year":"2015","journal-title":"Pervasive Mob. Comput."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.comcom.2015.10.006","article-title":"TDL: Two-dimensional localization for mobile targets using compressive sensing in wireless sensor networks","volume":"78","author":"Sun","year":"2016","journal-title":"Comput. Commun."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1016","DOI":"10.1109\/TCSI.2017.2766247","article-title":"Adaptive Matrix Design for Boosting Compressed Sensing","volume":"65","author":"Mangia","year":"2017","journal-title":"IEEE Trans. Circuits Syst. I Regul. Pap."},{"key":"ref_17","first-page":"79","article-title":"Sparse sampling decision-making based on compressive sensing for agricultural monitoring nodes","volume":"16","author":"Zhao","year":"2019","journal-title":"J. Chang. Univ. Ed."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1016\/j.adhoc.2015.08.014","article-title":"Toward cluster-based weighted compressive data aggregation in wireless sensor networks","volume":"36","author":"Abouei","year":"2016","journal-title":"Ad Hoc Netw."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.jnca.2015.11.002","article-title":"Energy-balanced compressive data gathering in Wireless Sensor Networks","volume":"61","author":"Lv","year":"2016","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.adhoc.2016.10.009","article-title":"Compressive sensing based random walk routing in wireless sensor networks","volume":"54","author":"Nguyen","year":"2017","journal-title":"Ad Hoc Netw."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.comnet.2016.06.029","article-title":"CCS: Energy-efficient data collection in clustered wireless sensor networks utilizing block-wise compressive sensing","volume":"106","author":"Teague","year":"2016","journal-title":"Comput. Netw."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2550","DOI":"10.1109\/JSEN.2017.2669081","article-title":"A Compressibility-Based Clustering Algorithm for Hierarchical Compressive Data Gathering","volume":"17","author":"Lan","year":"2017","journal-title":"IEEE Sens. J."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1016\/j.pmcj.2017.02.005","article-title":"An energy-efficient data gathering method based on compressive sensing for pervasive sensor networks","volume":"41","author":"Xiao","year":"2017","journal-title":"Pervasive Mob. Comput."},{"key":"ref_24","first-page":"26","article-title":"In-situ soil moisture sensing: Measurement scheduling and estimation using sparse sampling","volume":"11","author":"Wu","year":"2014","journal-title":"ACM Trans. Sens. Netw."},{"key":"ref_25","first-page":"1326","article-title":"Dynamic sampling scheduling policy for soil respiration monitoring sensor networks based on compressive sensing","volume":"43","author":"Wang","year":"2013","journal-title":"Sci. Sin. Inf."},{"key":"ref_26","first-page":"183","article-title":"Dynamic sampling method for wireless sensor network based on compressive sensing","volume":"37","author":"Song","year":"2017","journal-title":"J. Comput. Appl."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1016\/j.energy.2017.12.049","article-title":"Forecasting mid-long term electric energy consumption through bagging ARIMA and exponential smoothing methods","volume":"144","author":"Meira","year":"2018","journal-title":"Energy"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2231","DOI":"10.1109\/TKDE.2015.2411594","article-title":"Pietro Practical Data Prediction for Real-World Wireless Sensor Networks","volume":"27","author":"Raza","year":"2015","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_29","first-page":"581","article-title":"Anomaly Data Real-time Detection Method of Livestock Breeding Internet of Things Based on SW-SVR","volume":"157","author":"Duan","year":"2017","journal-title":"Nongye Jixie Xuebao\/Trans. Chin. Soc. Agric. Mach."},{"key":"ref_30","first-page":"2102","article-title":"Model-driven in-situ data compressive gathering","volume":"30","author":"Rao","year":"2018","journal-title":"ACTA Agric. Zhejiangensis"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1708","DOI":"10.1109\/JSEN.2015.2504106","article-title":"Data Reduction in Wireless Sensor Networks: A Hierarchical LMS Prediction Approach","volume":"16","author":"Tan","year":"2016","journal-title":"IEEE Sens. J."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.comcom.2017.08.002","article-title":"The impact of dual prediction schemes on the reduction of the number of transmissions in sensor networks","volume":"112","author":"Dias","year":"2017","journal-title":"Comput. Commun."},{"key":"ref_33","unstructured":"Raspberry Pi (2018, March 03). Available online: www.raspberrypi.org."},{"key":"ref_34","unstructured":"Das, S. (2017). Development of a Suitable Environment Control Chamber to Study Effects of Air Conditions on Physicochemical Changes During Withering and Oxidation of Tea. [Ph.D. Thesis, IIT]."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/12\/2654\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:57:48Z","timestamp":1760187468000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/12\/2654"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,12]]},"references-count":34,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2019,6]]}},"alternative-id":["s19122654"],"URL":"https:\/\/doi.org\/10.3390\/s19122654","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,6,12]]}}}