Long Short-Term Memory Based Model for Modeling Nicotine Consumption Using an Electronic Cigarette and Internet of Things Devices

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Model for Modeling Nicotine Consumption Using an Electronic Cigarette and Internet of Things Devices</title> <meta name="description" content="Long Short-Term Memory Based Model for Modeling Nicotine Consumption Using an Electronic Cigarette and Internet of Things Devices"> <meta name="keywords" content="Iot, activity recognition, automatic classification, unconstrained environment"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg 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class="card-body"><strong>Paper Count:</strong> 87407</div> </div> </div> </div> <div class="card publication-listing mt-3 mb-3"> <h5 class="card-header" style="font-size:.9rem">Long Short-Term Memory Based Model for Modeling Nicotine Consumption Using an Electronic Cigarette and Internet of Things Devices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamdi%20Amroun">Hamdi Amroun</a>, <a href="https://publications.waset.org/abstracts/search?q=Yacine%20Benziani"> Yacine Benziani</a>, <a href="https://publications.waset.org/abstracts/search?q=Mehdi%20Ammi"> Mehdi Ammi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users. <iframe src="https://publications.waset.org/abstracts/89965.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Iot" title="Iot">Iot</a>, <a href="https://publications.waset.org/abstracts/search?q=activity%20recognition" title=" activity recognition"> activity recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=automatic%20classification" title=" automatic classification"> automatic classification</a>, <a href="https://publications.waset.org/abstracts/search?q=unconstrained%20environment" title=" unconstrained environment"> unconstrained environment</a> </p> <a href="https://publications.waset.org/abstracts/89965/long-short-term-memory-based-model-for-modeling-nicotine-consumption-using-an-electronic-cigarette-and-internet-of-things-devices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/89965.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">224</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th 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Long Short-Term Memory Based Model for Modeling Nicotine Consumption Using an Electronic Cigarette and Internet of Things Devices