{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T19:12:59Z","timestamp":1767899579611,"version":"3.49.0"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,6,3]],"date-time":"2020-06-03T00:00:00Z","timestamp":1591142400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,6,3]],"date-time":"2020-06-03T00:00:00Z","timestamp":1591142400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2021,1]]},"DOI":"10.1007\/s12652-020-02051-6","type":"journal-article","created":{"date-parts":[[2020,6,3]],"date-time":"2020-06-03T17:01:49Z","timestamp":1591203709000},"page":"691-703","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":77,"title":["Modified ride-NN optimizer for the IoT based plant disease detection"],"prefix":"10.1007","volume":"12","author":[{"given":"Monalisa","family":"Mishra","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prasenjit","family":"Choudhury","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bibudhendu","family":"Pati","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,6,3]]},"reference":[{"issue":"11","key":"2051_CR1","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta R, Shaji A, Smith K et al (2012) SLIC super-pixels compared to state-of-the-art super-pixel methods\u201d. IEEE Trans Pattern Anal Mach Intell 34(11):2274\u20132282","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"3","key":"2051_CR2","first-page":"900","volume":"17","author":"RR Andrade","year":"2019","unstructured":"Andrade RR, Barbari M, Conti L, Tin\u00f4co IFF, Ba\u00eata FC, Teles Junior CGS, Zanetoni HHR, Vilela MO, Rossi G (2019) Alternative form to obtain the black globe temperature from environmental variables. Agron Res 17(3):900\u2013906","journal-title":"Agron Res"},{"issue":"1","key":"2051_CR3","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1109\/TIM.2018.2836058","volume":"68","author":"D Binu","year":"2019","unstructured":"Binu D, Kariyappa BS (2019) RideNN: a new rider optimization algorithm-based neural network for fault diagnosis in analog circuits. IEEE Trans Instrum Meas 68(1):2\u201326","journal-title":"IEEE Trans Instrum Meas"},{"issue":"1","key":"2051_CR4","first-page":"1","volume":"2","author":"G Brammya","year":"2019","unstructured":"Brammya G, Antely AS (2019) Face recognition using active appearance and type-2 fuzzy classifier. Multimed Res (MR) 2(1):1\u20138","journal-title":"Multimed Res (MR)"},{"issue":"6","key":"2051_CR5","doi-asserted-by":"publisher","first-page":"1159","DOI":"10.1007\/s11036-017-0866-1","volume":"22","author":"M Chen","year":"2017","unstructured":"Chen M, Yang J, Zhu X, Wang X, Liu M, Song J (2017) Smart home 2.0: innovative smart home system powered by botanical IoT and emotion detection. Mobile Netw Appl 22(6):1159\u20131169","journal-title":"Mobile Netw Appl"},{"key":"2051_CR6","doi-asserted-by":"crossref","unstructured":"Cimino D, Ferrero A, Queirolo L, Bellotti F, Berta R, Gloria AD (2016) A low-cost, open-source cyber physical system for automated, remotely controlled precision agriculture. In: International conference on applications in electronics pervading industry, environment and society, pp 191\u2013203","DOI":"10.1007\/978-3-319-47913-2_23"},{"key":"2051_CR7","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1016\/j.procs.2018.04.106","volume":"130","author":"K Foughali","year":"2018","unstructured":"Foughali K, Fathallah K, Frihida A (2018) Using cloud IOT for disease prevention in precision agriculture. Procedia Comput Sci 130:575\u2013582","journal-title":"Procedia Comput Sci"},{"issue":"6","key":"2051_CR8","first-page":"4219","volume":"13","author":"SA Hussain","year":"2018","unstructured":"Hussain SA, Hasan DR, Hussain SJ (2018) Classification and detection of plant disease using feature extraction methods. Int J Appl Eng Res 13(6):4219\u20134226","journal-title":"Int J Appl Eng Res"},{"key":"2051_CR9","doi-asserted-by":"crossref","unstructured":"Jones A, Ali U, Egerstedt M (2016) Optimal pesticide scheduling in precision agriculture. In: 2016 ACM\/IEEE 7th international conference on cyber-physical systems (ICCPS), pp 1\u20138","DOI":"10.1109\/ICCPS.2016.7479110"},{"key":"2051_CR10","doi-asserted-by":"crossref","unstructured":"Khirade SD, Patil AB (2015) Plant disease detection using image processing. In: 2015 International conference on computing communication control and automation (ICCUBEA), pp 768\u2013771","DOI":"10.1109\/ICCUBEA.2015.153"},{"issue":"3","key":"2051_CR11","first-page":"151","volume":"4","author":"N Krishnamoorthy","year":"2018","unstructured":"Krishnamoorthy N, Kalaimagal R, Shankar SG, Abdhul NS (2018) IoT based smart door locks. Int J Future Revolut Comput Sci Commun Eng 4(3):151\u2013154","journal-title":"Int J Future Revolut Comput Sci Commun Eng"},{"key":"2051_CR12","doi-asserted-by":"publisher","first-page":"975","DOI":"10.1016\/j.procs.2016.07.289","volume":"93","author":"VS Kumar","year":"2016","unstructured":"Kumar VS, Gogul I, Raj MD, Pragadesh SK, Sebastin JS (2016) Smart autonomous gardening rover with plant recognition using neural networks. Procedia Comput Sci 93:975\u2013981","journal-title":"Procedia Comput Sci"},{"key":"2051_CR13","doi-asserted-by":"crossref","unstructured":"Kwok J, Sun Y (2018) A smart IoT-based irrigation system with automated plant recognition using deep learning. In: Proceedings of the 10th international conference on computer modeling and simulation, pp 87\u201391","DOI":"10.1145\/3177457.3177506"},{"key":"2051_CR14","doi-asserted-by":"crossref","unstructured":"Mat I, Kassim MRM, Harun AN, Yusoff IM (2016) IoT in precision agriculture applications using wireless moisture sensor network. In: IEEE conference on open systems (ICOS), pp 24\u201329","DOI":"10.1109\/ICOS.2016.7881983"},{"key":"2051_CR15","unstructured":"Medela A, Cend\u00f3n B, Gonz\u00e1lez L, Crespo R, Nevares I (2013) IoT multiplatform networking to monitor and control wineries and vineyards. In: Future network and mobile summit. IEEE, pp 1\u201310"},{"key":"2051_CR16","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.knosys.2015.12.022","volume":"96","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S (2016) SCA: a sine cosine algorithm for solving optimization problems\u201d. Knowl Based Syst 96:120\u2013133","journal-title":"Knowl Based Syst"},{"key":"2051_CR17","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-020-01922-2","author":"P Murali","year":"2020","unstructured":"Murali P, Revathy R, Balamurali S, Tayade AS (2020) Integration of RNN with GARCH refined by whale optimization algorithm for yield forecasting: a hybrid machine learning approach. J Ambient Intell Hum Comput. https:\/\/doi.org\/10.1007\/s12652-020-01922-2","journal-title":"J Ambient Intell Hum Comput"},{"issue":"2","key":"2051_CR18","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1007\/s11277-017-5092-4","volume":"102","author":"SA Nandhini","year":"2018","unstructured":"Nandhini SA, Hemalatha R, Radha S, Indumathi K (2018) Web enabled plant disease detection system for agricultural applications using WMSN. Wirel Pers Commun 102(2):725\u2013740","journal-title":"Wirel Pers Commun"},{"issue":"11","key":"2051_CR19","doi-asserted-by":"publisher","first-page":"1452","DOI":"10.1109\/TPAMI.2004.110","volume":"26","author":"R Nock","year":"2004","unstructured":"Nock R, Nielsen F (2004) Statistical region merging. IEEE Trans Pattern Anal Mach Intell 26(11):1452\u20131458","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2051_CR20","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1007\/s10796-012-9374-9","volume":"17","author":"Z Pang","year":"2015","unstructured":"Pang Z, Chen Q, Han W, Zheng L (2015) Value-centric design of the internet-of things solution for food supply chain: value creation, sensor portfolio and information fusion. Inf Syst Front 17:289\u2013319","journal-title":"Inf Syst Front"},{"issue":"4","key":"2051_CR21","first-page":"295","volume":"4","author":"U Petruccelli","year":"2019","unstructured":"Petruccelli U, Antonello R (2019) Assessment of the drivers number as a tool for improving efficiency of public transport services. Ingegneria Ferroviaria 4(4):295\u2013315","journal-title":"Ingegneria Ferroviaria"},{"issue":"3","key":"2051_CR22","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1007\/s12469-017-0162-2","volume":"9","author":"U Petruccelli","year":"2017","unstructured":"Petruccelli U, Carleo S (2017) Cost models for local road transit. Public Transport 9(3):527\u2013548","journal-title":"Public Transport"},{"key":"2051_CR23","unstructured":"Plant Village Dataset (2018) https:\/\/github.com\/spMohanty\/PlantVillage-Dataset. Accessed 18 Dec 2018"},{"key":"2051_CR24","doi-asserted-by":"publisher","first-page":"1802","DOI":"10.1016\/j.procs.2015.02.137","volume":"46","author":"JD Pujari","year":"2015","unstructured":"Pujari JD, Yakkundimath R, Byadgi AS (2015) Image processing based detection of fungal diseases in plants. Procedia Comput Sci 46:1802\u20131808","journal-title":"Procedia Comput Sci"},{"issue":"1\u20132","key":"2051_CR25","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.compag.2006.01.004","volume":"52","author":"R Pydipati","year":"2006","unstructured":"Pydipati R, Burks TF, Lee WS (2006) Identification of citrus disease using color texture features and discriminant analysis. Comput Electron Agric 52(1\u20132):49\u201359","journal-title":"Comput Electron Agric"},{"key":"2051_CR26","first-page":"73","volume":"6","author":"CR Rad","year":"2015","unstructured":"Rad CR, Hancu O, Takacs IA, Olteanu G (2015) Smart monitoring of potato crop: a cyberphysical system architecture model in the field of precision agriculture. Agric Agric Sci Procedia 6:73\u201379","journal-title":"Agric Agric Sci Procedia"},{"key":"2051_CR27","first-page":"1392","volume":"13","author":"S Ramesh","year":"2018","unstructured":"Ramesh S, Rajaram B (2018) Iot based crop disease identification system using optimization techniques. ARPN J Eng Appl Sci 13:1392\u20131395","journal-title":"ARPN J Eng Appl Sci"},{"key":"2051_CR28","doi-asserted-by":"crossref","unstructured":"Rana K, Singh AV, Vijaya P (2018) A systematic review on different security framework for IoT. In: Proceedings of fifth international symposium on innovation in information and communication technology (ISIICT), pp 1\u20137","DOI":"10.1109\/ISIICT.2018.8613296"},{"key":"2051_CR29","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-020-01938-8","author":"PK Sethy","year":"2020","unstructured":"Sethy PK, Barpanda NK, Rath AK, Behera (2020) Nitrogen deficiency prediction of rice crop based on convolutional neural network. J Ambient Intell Hum Comput. https:\/\/doi.org\/10.1007\/s12652-020-01938-8","journal-title":"J Ambient Intell Hum Comput"},{"key":"2051_CR30","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.compag.2017.09.015","volume":"142","author":"JM Talavera","year":"2017","unstructured":"Talavera JM, Tob\u00f3n LE, G\u00f3mez JA, Culman MA, Aranda JM, Parra DT, Quiroz LA, Hoyos A, Garreta LE (2017) Review of IoT applications in agro-industrial and environmental fields. Comput Electron Agric 142:283\u2013297","journal-title":"Comput Electron Agric"},{"issue":"24","key":"2051_CR31","doi-asserted-by":"publisher","first-page":"16741","DOI":"10.1007\/s11042-015-2940-7","volume":"75","author":"W Tan","year":"2016","unstructured":"Tan W, Zhao C, Wu H (2016) Intelligent alerting for fruit-melon lesion image based on momentum deep learning. Multimed Tools Appl 75(24):16741\u201316761","journal-title":"Multimed Tools Appl"},{"key":"2051_CR32","doi-asserted-by":"crossref","unstructured":"Thorat A, Kumari S, Valakunde ND (2017) An IoT based smart solution for leaf disease detection. In: 2017 international conference on big data, IoT and data science (BID), Pune, pp 193\u2013198","DOI":"10.1109\/BID.2017.8336597"},{"key":"2051_CR33","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-019-01591-w","author":"M Turkoglu","year":"2019","unstructured":"Turkoglu M, Hanbay D, Sengur A (2019) Multi-model LSTM-based convolutional neural networks for detection of apple diseases and pests. J Ambient Intell Hum Comput. https:\/\/doi.org\/10.1007\/s12652-019-01591-w","journal-title":"J Ambient Intell Hum Comput"},{"issue":"1","key":"2051_CR34","first-page":"27","volume":"1","author":"N Veeraiah","year":"2018","unstructured":"Veeraiah N, Krishna BT (2018) Intrusion detection based on piecewise fuzzy C-means clustering and fuzzy na\u00efve bayes rule. Multimed Res (MR) 1(1):27\u201332","journal-title":"Multimed Res (MR)"},{"key":"2051_CR35","doi-asserted-by":"publisher","first-page":"866","DOI":"10.1016\/j.ijleo.2017.11.190","volume":"157","author":"S Zhang","year":"2018","unstructured":"Zhang S, Wang H, Huang W, You Z (2018) Plant diseased leaf segmentation and recognition by fusion of superpixel, K-means and PHOG. Optik Int J Light Electron Opt 157:866\u2013872","journal-title":"Optik Int J Light Electron Opt"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-020-02051-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-020-02051-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-020-02051-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,3]],"date-time":"2021-06-03T00:51:07Z","timestamp":1622681467000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-020-02051-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,3]]},"references-count":35,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["2051"],"URL":"https:\/\/doi.org\/10.1007\/s12652-020-02051-6","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"value":"1868-5137","type":"print"},{"value":"1868-5145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,3]]},"assertion":[{"value":"14 June 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 April 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 June 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}