IoT based intelligence for proactive waste management in Quick Service Restaurants

Aytac Kerem; Korcak Omer

摘要

Quick Service Restaurant industry is a massive sector which has a huge and ever increasing share in the global food market. Efficient management of resources is crucial to provide service optimization and to avoid massive amount of wastes in such a huge domain. This requires fully automated intelligence by using the power of the Internet of Things (IoT), instead of human based methods that are inefficient and prone to errors. In an IoT platform, edge computing is a vital technology to provide low latency, less redundancy, resource utilization, extra security and real time decisions. In this paper, an edge oriented IoT architecture for Quick Service Restaurants is proposed. In the proposed architecture, data is collected from a variety of wireless sensor nodes and data sources and processed at the edge to make predictions, to create timely and meaningful alerts and to make some intelligent decisions with an aim of waste management and reduction. For this purpose, it is mainly focused on anomaly/outlier detection and production service level estimation by incorporating lightweight clustering and classification techniques. Several experiments are performed in a real restaurant environment and the results show that the IoT based automation system is capable of correctly deciding on (in advance) production level, as well as triggering alerts in case of any kind of anomalous waste conditions. (C) 2020 Elsevier Ltd. All rights reserved.

机译：快速服务餐厅行业是一个大规模的部门，在全球食品市场中具有巨大而不断增加的份额。有效管理资源至关重要，以提供服务优化，并避免在这种庞大的域中的大量废物。这需要通过使用Internet（IoT）的权力来完全自动化智能，而不是基于基于人的方法，而不是效率低下并且容易出错。在一个IOT平台中，边缘计算是一种重要的技术，可以提供低延迟，更冗余，资源利用，额外的安全性和实时决策。在本文中，提出了一个用于快速服务餐厅的优势IOT架构。在所提出的架构中，数据从各种无线传感器节点和数据源收集并在边缘处理以进行预测，以创建及时和有意义的警报，并制定一些智能决策，并具有废物管理和减少的智能决策。为此目的，它主要专注于通过结合轻量级聚类和分类技术来集中在异常/异常检测和生产服务水平估计。在真实的餐厅环境中进行了几个实验，结果表明，基于物联网的自动化系统能够正确地决定（预先）生产水平，以及在任何异常废物条件下触发警报。（c）2020 elestvier有限公司保留所有权利。

IoT based intelligence for proactive waste management in Quick Service Restaurants

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