The growing number of fatalities among miners caused by toxic gases puts pressure on the mining industry; innovative approaches are required to improve underground miners' health. Toxic gases are very often released in underground mines and cannot easily be detected by human senses. This paper investigates the presence of the inherent types of toxic fumes in critical regions and their suspension and trends in the air and intends to generate knowledge that will assist in preventing miners from contracting diseases. The development of intelligent decision support systems is still in its infancy. Knowledge of how to make them profitable in improving miners' safety is largely lacking. An autonomous remote monitoring framework of wireless sensor networks, which integrates mobile sensing and Ohm's law, coupled with ambient intelligence governing decision-making for miners, is developed. The framework has been investigated in indoor scenarios and successfully deployed for real-life application in an aeronautic engine test cell environment, such as those typically found in underground mines. Useful demonstrations of the system were carried out to provide similar knowledge to safeguard engineers from the inhalation of toxic gases. This provides early warning for safety agents. The system has proven to be suitable for deployment in underground mines.

Purpose – The internet provides a mechanism by which buyers and sellers meet in order to exchange goods and services online with the utmost convenience. However, there are many risks associated with the internet which, if left unattended, could continue deterring the adoption of e-commerce. These risks ultimately diminish online consumer trust in e-commerce. Web assurance models have been designed in an attempt to encourage online consumer trust through assurance. Unfortunately, many of these models have been inadequate in certain areas and this research aims to improve on them. Design/methodology/approach – It presents a comprehensive empirical survey on trustworthiness issues and e-commerce assurance models and proposes a new compliance-based e-commerce assurance model that integrates adaptive legislation, adaptive e-commerce-related standards and cooperative rating. The intelligent cooperative rating is based on the analytic hierarchy process and page-ranking techniques. Findings – Some findings of this research study influence the thinking that some of the untrustworthy sites are posing as trustworthy sites because they display web seals. The findings can be used as a reference guide to understand e-commerce assurance models, as well as the effectiveness of ensuring the trustworthiness of these models. Practical implications – The research presents deployment analysis on the use of the proposed compliance model through real life scenarios categorized as trustworthy and untrustworthy e-commerce web sites. Originality/value – This research is relevant to information management and computer security in e-commerce as a development of a newly proposed e-commerce assurance model for trustworthiness safety inspections and knowledge generation as a reference guide to understand e-commerce trustworthiness in general and e-commerce assurance models in particular detail.

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Purpose – The objective of this paper is to present a comprehensive literature survey on dyslexic learners and to propose a model for integrated assistive technology of dyslexic learners. Design/methodology/approach – The use of the proposed model through real-life scenarios categorized as “phonological, reading and writing scenarios”. We have also surveyed some systems for use with dyslexic learners currently in use and have compared them on the basis of number of barriers, technological innovation, age group and fostering. Findings – Dyslexic learners are characterized by slow learning, poor handwriting, poor spelling skills and difficulties in planning, organizing, revising and editing texts; technology plays a major role in the educational environment; it has become crucial in impacting knowledge across the globe; and open research issues and challenges that have to be addressed in the design of the current dyslexic system have been presented in detail. Research limitations/implications – Full implementation of the proposed model and its application in developing countries. Practical implications – The system improves the phonological awareness, reading and writing skills of dyslexic learners and it provides a solution for children as well as adults with dyslexia. Social implications – This survey can be used as a reference guide to understand learning barriers and intelligent systems for dyslexic learners and to promote the use of these in schools for those with learning disabilities who need assistive technologies. Originality/value – Development of a newly proposed integrated intelligent assistive system for dyslexic learners; knowledge generation as a reference guide to understand dyslexic learning ability in general and an intelligent assistive dyslexic system in particular; and survey of open research issues and challenges to further research in intelligent dyslexic systems.

Cloud robotics is a paradigm that allows for robots to offload computationally intensive and data storage requirements into the cloud by providing a secure and customizable environment. The challenge for cloud robotics is the inherent problem of cloud disconnection. A major assumption made in the development of the current cloud robotics frameworks is that the connection between the cloud and the robot is always available. However, for multi-robots working in heterogeneous environments, the connection between the cloud and the robots cannot always be guaranteed. This work serves to assist with the challenge of disconnection in cloud robotics by proposing a survivable cloud multi-robotics (SCMR) framework for heterogeneous environments. The SCMR framework leverages the combination of a virtual ad hoc network formed by robot-to-robot communication and a physical cloud infrastructure formed by robot-tocloud communications. The quality of service (QoS) on the SCMR framework was tested and validated by determining the optimal energy utilization and time of response (ToR) on drivability analysis with and without cloud connection. The design trade-off, including the result, is between the computation energy for the robot execution and the offloading energy for the cloud execution.

Achieving situation recognition in ubiquitous sensor networks (USNs) is an important issue that has been poorly addressed by both the research and practitioner communities. This paper describes some steps taken to address this issue by effecting USN middleware intelligence using an emerging situation awareness (ESA) technology. We propose a situation recognition framework where temporal probabilistic reasoning is used to derive and emerge situation awareness in ubiquitous sensor networks. Using data collected from an outdoor environment monitoring in the city of Cape Town, we illustrate the use of the ESA technology in terms of sensor system operating conditions and environmental situation recognition.

Underground mining operations are carried out in hazardous environments. To prevent disasters from occurring, as often as they do in underground mines, and to prevent safety routine checkers from disasters during safety inspection checks, multirobots are suggested to do the job of safety inspection rather than human beings and single robots. Multirobots are preferred because the inspection task will be done in the minimum amount of time. This paper proposes a cooperative behaviour for a multirobot system (MRS) to achieve a preentry safety inspection in underground terrains. A hybrid QLACS swarm intelligent model based on Q-Learning (QL) and the Ant Colony System (ACS) was proposed to achieve this cooperative behaviour in MRS. The intelligent model was developed by harnessing the strengths of both QL and ACS algorithms. The ACS optimizes the routes used for each robot while the QL algorithm enhances the cooperation between the autonomous robots. A description of a communicating variation within the QLACS model for cooperative behavioural purposes is presented. The performance of the algorithms in terms of without communication, with communication, computation time, path costs, and the number of robots used was evaluated by using a simulation approach. Simulation results show achieved cooperative behaviour between robots.

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