Department of Mechanical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia.
Department of Management, Faculty of Business and Economics, Universiti Malaya, Kuala Lumpur 50603, Malaysia.
Int J Environ Res Public Health. 2023 Jan 11;20(2):1319. doi: 10.3390/ijerph20021319.
Although alcohol consumption may produce effects that can be beneficial or harmful, alcohol consumption prevails among communities around the globe. Additionally, alcohol consumption patterns may be associated with several factors among communities and individuals. Numerous technologies and methods are implemented to enhance the detection and tracking of alcohol consumption, such as vehicle-integrated and wearable devices. In this paper, we present a cellular-based Internet of Things (IoT) implementation in a breath analyzer to enable data collection from multiple users via a single device. Cellular technology using hypertext transfer protocol (HTTP) was implemented as an IoT gateway. IoT integration enabled the direct retrieval of information from a database relative to the device and direct upload of data from the device onto the database. A manually developed threshold algorithm was implemented to quantify alcohol concentrations within a range from 0 to 200 mcg/100 mL breath alcohol content using electrochemical reactions in a fuel-cell sensor. Two data collections were performed: one was used for the development of the model and was split into two sets for model development and on-machine validation, and another was used as an experimental verification test. An overall accuracy of 98.16% was achieved, and relative standard deviations within the range from 1.41% to 2.69% were achieved, indicating the reliable repeatability of the results. The implication of this paper is that the developed device (an IoT-integrated breath analyzer) may provide practical assistance for healthcare representatives and researchers when conducting studies involving the detection and data collection of alcohol consumption patterns.
尽管饮酒可能产生有益或有害的影响,但酒精消费在全球各地的社区中普遍存在。此外,酒精消费模式可能与社区和个人的多个因素有关。许多技术和方法被用于增强酒精消费的检测和跟踪,例如车载和可穿戴设备。在本文中,我们提出了一种基于蜂窝的物联网 (IoT) 在呼吸分析器中的实现,以允许通过单个设备从多个用户收集数据。使用超文本传输协议 (HTTP) 的蜂窝技术被实现为 IoT 网关。IoT 集成使我们能够直接从与设备相关的数据库中检索信息,并直接将设备上的数据上传到数据库。我们实施了一个手动开发的阈值算法,使用燃料电池传感器中的电化学反应来定量 0 到 200 mcg/100 mL 呼气酒精含量范围内的酒精浓度。进行了两次数据收集:一次用于模型的开发,并分为两组用于模型开发和机器上的验证,另一次用于实验验证测试。实现了 98.16%的总体准确率,并且在 1.41%至 2.69%的范围内实现了相对标准偏差,表明结果具有可靠的可重复性。本文的意义在于,所开发的设备(集成了物联网的呼吸分析器)可能为医疗保健代表和研究人员在进行涉及酒精消费模式检测和数据收集的研究时提供实际帮助。