Wi-Wheat+: Contact-free wheat moisture sensing with commodity WiFi based on entropy

Jayas, 2012, Storing grains for food security and sustainability, Agric. Res., 1, 21, 10.1007/s40003-011-0004-4 Nelson, 2016, Historical development of grain moisture measurement and other food quality sensing through electrical properties, IEEE Instrum. Meas. Mag., 19, 16, 10.1109/MIM.2016.7384955 Nelson, 2000, Sensing moisture content in grain, IEEE Instrum. Meas. Mag., 3, 17, 10.1109/5289.823818 Vasisht, 2017, FarmBeats: an IoT platform for data-driven agriculture, 515 American Society of Agricultural Engineers, 2001, 67 Wang, 2011, A grain moisture detecting system based on capacitive sensor, Int. J. Digital Content Technol. Appl., 5, 203, 10.4156/jdcta.vol5.issue3.20 Gan, 2018, Development of grain moisture detecting instrument based on friction resistance method, J. Agric. Mech. Res., 40, 91 Liu, 2015, Research on online moisture detector in grain drying process based on V/F conversion, Hindawi Math. Problems Eng., 2015 Nelson, 2000, Using cereal grain permittivity for sensing moisture content, IEEE Trans. Instrum. Meas., 49, 470, 10.1109/19.850378 Kim, 2006, Simple instrument for moisture measurement in grain by free-space microwave transmission, Trans. ASABE (Am. Soc. Agric. Biol. Eng.), 49, 1089 Yang, 2000, Study on on-line measurement of grain moisture content by neutron gauge, Trans. Chin. Soc. Agric. Eng., 16, 99 Nath K, 2017, Non-destructive methods for the measurement of moisture contents–a review, Sens. Rev., 37, 71, 10.1108/SR-01-2016-0032 Zhu, 2016, CSI-based Wi-Fi environment sensing, J. Nanjing Univ. Posts Telecommun. (Nat. Sci. Ed.), 36, 95 Wang, 2018, RF sensing for Internet of Things: a general deep learning framework, IEEE Commun. Mag., 56, 62, 10.1109/MCOM.2018.1701277 Yang, 2013, From RSSI to CSI: indoor localization via channel response, ACM Comput. Surv., 46, 25, 10.1145/2543581.2543592 Yang, 2018, Wi-Wheat: contact-free wheat moisture detection with commodity WiFi, 1 Stuart, 2004, Principles for microwave moisture and density measurement in grain and seed, J. Microw. Power Electromagn. Energy, 39, 107 Xiao, 2012, FIFS: fine-grained indoor fingerprinting system, 1 Wang, 2017, CSI-based fingerprinting for indoor localization: a deep learning approach, IEEE Trans. Veh. Technol., 66, 763 Wang, 2016, CSI phase fingerprinting for indoor localization with a deep learning approach, IEEE Internet Things J., 3, 1113, 10.1109/JIOT.2016.2558659 Wang, 2017, BiLoc: Bi-modality deep learning for indoor localization with 5GHz commodity Wi-Fi, IEEE Access J., 5, 4209, 10.1109/ACCESS.2017.2688362 Wang, 2021, Indoor fingerprinting with bimodal CSI tensors: a deep residual sharing learning approach, IEEE Internet Things J., 8, 4498, 10.1109/JIOT.2020.3026608 Wang, 2020, Deep convolutional neural networks for indoor localization with CSI images, IEEE Trans. Netw. Sci. Eng., 7, 316, 10.1109/TNSE.2018.2871165 Wang, 2014, E-Eyes: device-free location-oriented activity identification using fine-grained WiFi signatures, 617 Wang, 2014, We can hear you with Wi-Fi, 593 Wang, 2015, Understanding and modeling of WiFi signal based human activity recognition, 65 Wang, 2017, WiFall: device-free fall detection by wireless networks, IEEE Trans. Mobile Comput., 16, 581, 10.1109/TMC.2016.2557792 Wang, 2017, RT-Fall: a real-time and contactless fall detection system with commodity WiFi devices, IEEE Trans. Mobile Comput., 16, 511, 10.1109/TMC.2016.2557795 Wang, 2017, PhaseBeat: exploiting CSI phase data for vital sign monitoring with commodity WiFi devices, 1230 Wang, 2017, TensorBeat: tensor decomposition for monitoring multi-person breathing beats with commodity WiFi, ACM Trans. Intell. Syst. Technol., 9, 8.1 Zhong, 2017, Wi-Fire: device-free fire detection using WiFi networks, 1 Wu, 2016, Wi-Metal: detecting metal by using wireless networks, 1 Zhou, 2014, LiFi: line-of-sight identification with WiFi, 2688 Yang, 2018, Multi-class wheat moisture detection with 5GHz Wi-Fi: a deep LSTM approach, 1 Suykens, 1999, Least squares support vector machine classifiers, Neural Process. Lett., 9, 293, 10.1023/A:1018628609742 C.-C. Chang and C.-J. Lin, “LIBSVM – A Library for Support Vector Machines,” [online] Available: https://www.csie.ntu.edu.tw/∼cjlin/libsvm/. Gong, 2020, Integrating ultra weak luminescence properties and multi-scale permutation entropy algorithm to analyze freshness degree of wheat kernel, Elsevier Optik J., 218 Hu, 2019, MiFi: device-free wheat mildew detection using off-the-shelf WiFi devices, 1