Lizong Zhang

A Decision Support Application in Tracking Construction Waste Using Rule-based Reasoning and RFID Technology

AbstractProtection of the environment is currently a high profile concern and this is resulting in more effective recycling and reuse of materials. This paper outlines a research project for developing and using a ‘Technology Hub’ framework combining Computational Intelligence – Rule-based Reasoning technology and Radio Frequency Identification (RFID) technology in the waste management sector. This framework has been developed using a case study based on a local waste recycling company. The project aims to help recycling companies in tracking, scheduling and intelligently handling incidents of waste movement in order to prevent fly-tipping and improve their management efficiency. Finally, the development procedure for a smart plasterboard waste management system is outlined, which includes a detailed discussion concerning the Rule-based Reasoning system design. This application provides a solution that a company can use to monitor the fleet/waste status and also generate decision support automatically in ...

Application of RFID and Mobile Technology to Plaster Board Waste in the Construction Industry

1. Introduction Protection of the environment is one of the most sensitive topics of recent years and recognition of its importance is resulting in more effective recycling and reuse of material. Simply disposing of waste through landfill or burning, as was historically the case, will damage our environment. Nowadays, a number of government initiatives and environmental pressure groups are seeking more environmental, socially responsible methods of disposal. Undoubtedly, recycling is the best solution for protecting our environment by ‘waste management’. In general, waste management is the administration of collection, transport, processing, recycling and/or disposal of waste materials(McBean et al., 1995). Currently, it usually includes reduction and auditing activities for the protection of human health and the environment by producing less waste and by using it as a resource wherever possible. This type of waste management is known as ‘sustainable waste management’– reduction, re-use, recycling, composting and using waste as a source of energy (DEFRA, 2007). Today, waste generation and disposal has become a serious problem. Each year, approximately 335 Mt of waste are produced in the UK most of which is produced in England. In 2005, 272 Mt were produced in England, much more than Scotland, Wales and Northern Ireland, which produce less than 25% of the total UK waste (DEFRA, 2007). Information from the Environment Agency (EA) and SEPA (Scotland’s Environmental Regulator and Adviser) indicated there were 4.12 Mt of hazardous waste produced in England and Wales (EA, 2007), with an additional 4,430 tonnes produced in Scotland (SEPA(Scotland), 2007). In 2006, this increased to 6 Mt in England and Wales (EA, 2008a). In general, waste is a combination of many types of material, and most of them are harmful and polluting. Waste takes many years to break down, and can pollute water courses and the land even when it is carefully disposed of, especially the hazardous or controlled waste. However, fly-tipping and incorrect land filling of these types of waste will cause heavy pollution and damage to the environment. The UK produces over 1 million tonnes (Mt) of plasterboard waste per annum, of which only up to 7% is being recycled whilst the majority has been land filled which causes a potential environmental problem. Plasterboard waste contains a high percentage of gypsum which has resulted in serious problems because of the emission of hydrogen sulphide gas (H2S) once it is land filled with organic waste. According to DEFRA (Department for Environment, Food and Rural Affairs), it can be anticipated that the volume of plasterboard waste will increase over the next 15 years due to the expansion of usage and the rise in construction projects. Another example is medical waste; it usually contains infectious materials, drugs and sharp objects such as syringes, which are undoubtedly harmful waste that contains a large number of viruses, bacteria and harmful chemical reagents. In the UK, only a few recycling facilities are available in England, and it is usual for the recycling companies to take plasterboard waste from construction or demolition sites themselves, and charge a transportation fee. Depending on the distance to the recycling facilities, transportation fees can be expensive, and exceed the landfill mono-cell costs. Consequently, increasing recycling is a viable route to prevent environmental problems. To improve the recycling rate, a tracking and auditing system is needed to prevent fly tipping and other illegal disposal. A novel waste management prototype is outlined based on identification technology, current waste management process and reasoning techniques. In this chapter, RFID (Radio Frequency Identification) technology is introduced which can potentially improve the waste management efficiency. Radio Frequency Identification (RFID) is an automatic identification technology used in assets tracking and logistics support in supply chain management by substituting barcodes with RFID tags.

A self-adaptive distributed decision support model for Internet of Things applications

The term of Internet of Things (IoT) is an emerging concept that has already made an impact on many research domains by providing new solutions and ideas. However, we noticed that many IoT applications are more focused on the ‘communication’ part and are still relatively weak in ‘intelligent’ aspects. Consequently, in this paper we proposed an approach for a self-adaptive distributed decision support model to provide more intelligent support for IoT applications. The model is designed with three major approaches: an artificial neural network (ANN) for environment recognition, knowledge merging to create a local knowledge base and expert systems technology for decision making. In addition, a self-adaption feature is introduced to fix any possible improper usage of knowledge that may be caused by inaccuracies in the environment recognition. This strategy was confirmed in an experiment with a local Chinese medical clinical trials centre, in which the results indicate it may improve the accuracy of decisions from 42% to about 85%.