Elsevier

Waste Management

Volume 68, October 2017, Pages 434-448
Waste Management

Internet of things and Big Data as potential solutions to the problems in waste electrical and electronic equipment management: An exploratory study

https://doi.org/10.1016/j.wasman.2017.07.037Get rights and content

Highlights

  • Major problems in current WEEE management have been identified.

  • Communication technologies enabling smart WEEE management are described.

  • Framework of implementing the IoT and the Big Data technologies is proposed.

  • Application scenarios based on real-world cases are constructed and discussed.

  • Challenges as well as future research opportunities are identified.

Abstract

Management of Waste Electrical and Electronic Equipment (WEEE) is a vital part in solid waste management, there are still some difficult issues require attentionss. This paper investigates the potential of applying Internet of Things (IoT) and Big Data as the solutions to the WEEE management problems. The massive data generated during the production, consumption and disposal of Electrical and Electronic Equipment (EEE) fits the characteristics of Big Data. Through using the state-of-the-art communication technologies, the IoT derives the WEEE “Big Data” from the life cycle of EEE, and the Big Data technologies process the WEEE “Big Data” for supporting decision making in WEEE management. The framework of implementing the IoT and the Big Data technologies is proposed, with its multiple layers are illustrated. Case studies with the potential application scenarios of the framework are presented and discussed. As an unprecedented exploration, the combined application of the IoT and the Big Data technologies in WEEE management brings a series of opportunities as well as new challenges. This study provides insights and visions for stakeholders in solving the WEEE management problems under the context of IoT and Big Data.

Introduction

Waste Electrical and Electronic Equipment (WEEE), or known as e-waste, has become one of the largest and fastest growing waste stream in the world (Rahimifard et al., 2009). At global level, WEEE has an average annual growth rate of 3–5% which corresponds almost three times the growth of municipal solid waste in general (Rahimifard et al., 2009, Duygan and Meylan, 2015). The global quantity of WEEE is estimated to be 41.8 Mt in 2014, 43.8 Mt in 2015, and it is expected to grow to 49.8 Mt in 2018 (Baldé et al., 2015). With a rapid annual growth rate around 13–15% (Gu et al., 2016a), China generated approximately 8.53 Mt WEEE in 2014 and has already become the largest WEEE generator worldwide (Zeng et al., 2016a, Zeng et al., 2016b).

WEEE contains various valuable resources as well as a wide range of pollutants (Dewulf et al., 2010, Zeng et al., 2017b). Owing to limited reserves (Du and Graedel, 2011), recovering materials from WEEE is a promising practice for sustainable development of the related industry. For examples, the rapid development of electric vehicles demands a higher recycling rate (over 90%) for lithium (Zeng and Li, 2013) and cobalt (Zeng and Li, 2015), and recycling indium from spent liquid crystal displays (LCDs) is of critical importance to support continuous production of new LCDs (Zhang et al., 2015a). WEEE recycling is regarded as a profitable business (Cucchiella et al., 2015, Zeng et al., 2016a, Zeng et al., 2016b). Recovering precious metals such as gold, can sustain the profitability of a WEEE recycling plant (Cucchiella et al., 2016). Asides from resource sustainability and economical gains, environmental impacts of WEEE can be significantly reduced through recycling those metal contents (Wäger et al., 2011). Moreover, recycling is proved to be the best option of disposing polymeric fractions in WEEE from an life cycle environmental perspective (Wäger and Hischier, 2015), and the end markets of these recycled plastics are expanding (Gu et al., 2017a). However, improper treatments of WEEE lead to catastrophic results, as environmental pollutions caused by WEEE recycling are frequently reported (Tao et al., 2015, Awasthi et al., 2016, Wu et al., 2016). Consequently, physical health of the nearby residents and the workers is in great peril due to exposure to heavy metals and persistent organic pollutants (POPs) released from WEEE recycling sites (Huang et al., 2016, Lu et al., 2016a, Wang et al., 2016a), especially that of children (Tang et al., 2015, Zeng et al., 2016b).

Recognising the delicate nature and the importance of recycling, the management of WEEE has become a topical issue in solid waste management. In this study, we discuss the potential of using big data technologies in solving existing problems in WEEE management. This paper is organised as follows: the current problems are depicted and analysed in Section 2, the characteristics of the WEEE “Big Data” are examined in Section 3, the state-of-the-art communication technologies for acquiring the WEEE “Big Data” are illustrated in Section 4, the framework of implementing the IoT and the Big Data technologies in WEEE management is proposed in Section 5, two application scenarios based on real-world cases are delivered in Section 6, both the opportunities and challenges discussed according to different perspectives in Section 7, the conclusions are given in Section 8 while the shortcoming of this study is also identified.

Section snippets

Ineffective legislation

Across the globe, governments have proposed laws, regulations and policies to facilitate WEEE management. Yet, according to the extent literature, the effectiveness of these legislations remains questionable.

Big Data in WEEE management

All the articles focus on WEEE management offered recommendations from different perspectives. In principal, the WEEE recycling system is regarded as a reverse logistics system (Cao et al., 2016a, as shown in Fig. 1) and a supply chain (Georgiadis and Besiou, 2008, Gu et al., 2016a), and hence information is as important as material (Kaipia, 2013). Installing Management Information Systems (MIS) is a prerequisite for WEEE disposers to gain the subsidy from the Chinese government (Cao et al.,

Communication technologies

Adapting the Big Data into WEEE management required for the involvement of several enabling communication technologies. In this section, the most relevant technologies are selected and discussed. Instead of providing a comprehensive survey of each technology, the aim of this section is to provide a picture of the roles they will likely play in the WEEE “Big Data” management framework, which is later presented in Section 5.

Framework for implementation

Big data collecting, Big Data processing, Big Data visualisation and Big Data analytics are the Big Data technologies used in Service and Manufacturing Supply Chain Management (SM-SCM) (Zhong et al., 2016a). As discussed above, WEEE management system can be regarded as SC-SCM, since it is heavily involved with in a wide range of equipments and human activities. A framework of implementing big data and related technologies for WEEE management is proposed, as shown in Fig. 2. The framework can be

Case studies

Implementing the IoT and the Big Data technologies will significantly reform the current WEEE recycling system towards sustainability. This section provides some case studies with the potential WEEE management scenarios of applying the framework of the IoT and the Big Data.

Challenges and research opportunities

Introduction of the IoT and the Big Data technologies in WEEE management brings plenty of potential benefits in improving the current system, expanding business model and increasing overall efficiency. However, there are some obvious challenges in implementing the IoT and the Big Data in WEEE management. Yet, challenges are accompanied by opportunities. In this section, the challenges associated with implementation of the IoT and the Big Data technologies are discussed. In general, the

Conclusions

With increasing production and consumption, WEEE is becoming a major concern in waste management. The paper aims to provide a comprehensive view of the potential application of the IoT and the Big Data technologies in WEEE management. The problems in current WEEE recycling system are identified and discussed. Some selected communication technologies and their potential roles in WEEE management are presented. A framework of implementing the IoT and the Big Data technologies in WEEE management is

Acknowledgements

This work is financially supported by National Natural Science Foundation of China (71271200 and 71671180), National Science and Technology Major Project (2016ZX05040-001), Industrial Technology Innovation and Industrialisation of Science and Technology Project (2014A35001-2) and Green Manufacturing System Integration Project 2016 of Chinese Ministry of Industry and Information.

The authors would like to thank the Editor and the anonymous reviewers for their constructive comments and suggestions

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