Using Drones in Internal and External Audits: An Exploratory Framework

Recently the FAA relaxed restrictions on the use of drones or Unmanned Aircraft Systems (UASs) for commercial purposes. Markets for commercial drone use are in the technology trigger phase of the Gartner Group’s Hyper Cycle, with developments occurring rapidly in real estate, agriculture (farming), the film industry, insurance, and other areas. Examination and inspection applications of drones have been proposed in heavy industry and cell tower inspection. Previous research suggests an incremental structure for implementing technological innovations such as continuous auditing (CA). In this paper these proposals are expanded to include the additional requirements to add drone technologies. This structure is extended here by (1) defining the use of drones in audit environments, with emphasis on the continuous versus occasional use of drone technologies, (2) extending the technical adoption architecture to include the use of drones, and (3) considering the types of drone usages amenable to both internal and external audits. A specific architecture is proposed here to prototype inventory counts in large warehouses or open-air inventories and that satisfies the suggested requirements. Additionally, this proposal adds value to the current research by extending the discussion of technology adoption in the Alles, Kogan, and Vasarhelyi (2008) paper to include the use of drones in many different audit environments by enumerating the usage types of drones in audit settings and by considering the prototype of such a system

Automating Production Process Data Acquisition Towards Spaghetti Chart 4.0

Automation of logistics and production processes is one of the significant goals of the Industry 4.0 movement. Thus, this study uses the automatic data acquisition approach to automatically create Spaghetti Charts (SC), decrease the required time spent on collecting data, and provide a fast analysis (feedback). Smartphone technology used for drawing the automated spaghetti diagram has potential drawbacks related to safety, security, the privacy of organizations, and independency. So, Method Time Measurement 4.0 and RStudio software are used to collect the real data and draw the spaghetti chart, respectively, as an alternative solution. The experiment results for four scenarios (different Facility layouts and processes) prove that the approach is competitive, with cycle time reduction exceeding 40% less than the conventional facility layout and process plan. The proposed solution of the wearable device is promising for replacing smartphone technology with smart spaghetti chart systems

Campus Safety Data Gathering, Classification, and Ranking Based on Clery-Act Reports

Most existing campus safety rankings are based on criminal incident history with minimal or no consideration of campus security conditions and standard safety measures. Campus safety information published by universities/colleges is usually conceptual/qualitative and not quantitative and are based-on criminal records of these campuses. Thus, no explicit and trusted ranking method for these campuses considers the level of compliance with the standard safety measures. A quantitative safety measure is important to compare different campuses easily and to learn about specific campus safety conditions. In this thesis, we utilize Clery-Act reports of campuses to automatically analyze their safety conditions and generate a safety rank based on these reports. We first provide a survey of campus safety and security measures. We utilize our survey results to provide an automated data-gathering method for capturing standard campus safety data from Clery-act reports. We then utilize the collected information to classify existing campuses based on their safety conditions. Our research model is also capable to predict the safety rank of campuses based on their Clery-Act report by comparing it to existing Clery-Act reports of other campuses and reported rank on public resources. Our research on this thesis uses a number of languages, tools, and technologies such as Python, shell scripts, text conversion, data mining, spreadsheets, and others. We provide a detailed description of our research work on this topic, explain our research methodology, and finally describe our findings and results. This research contributes to the automated campus safety data generation, classification, and ranking

Implementing QR Code Technology in Medical Device Pacakage

The medical device industry strives to improve the delivery of key device information through the package to patients, doctors and end users. To achieve this goal Indications For Use (IFU) and user manuals have been major tools and are necessary components required in Medical Device Package according to Food and Drug Administration (FDA) standards. Historically there have been challenges caused by packaging information materials aspects such as manufacturing, transportation and translation. The need for extensive packaging and labelling has ultimately contributed to increased cost of manufacturing for devices. It is also important to know what information a customer needs and recognize that the safety of the consumer is of the utmost importance. The development and implementation of new technologies and procedures in a medical device industry may be complicated and slow but it is a necessity to improve safety and provide maximum comfort to the end user. Barcodes and Two Dimensional code have been used in the medical device industry for tracking purposes; however, the focus of this thesis was using QR codes (two-Dimensional barcode) in medical device package without IFU, user guides and manuals to enhance patient safety, reduce cost and enhance the breadth of information available to the ultimate users. Access to the information was achieved by just taking a picture or scanning the QR code which was printed on a medical device package. This thesis also assesses the feasibility of implementing the QR code technology on medical device package and a case study is conducted that elaborates on the cost analysis

Enhanced Living Environments

This open access book was prepared as a Final Publication of the COST Action IC1303 “Algorithms, Architectures and Platforms for Enhanced Living Environments (AAPELE)”. The concept of Enhanced Living Environments (ELE) refers to the area of Ambient Assisted Living (AAL) that is more related with Information and Communication Technologies (ICT). Effective ELE solutions require appropriate ICT algorithms, architectures, platforms, and systems, having in view the advance of science and technology in this area and the development of new and innovative solutions that can provide improvements in the quality of life for people in their homes and can reduce the financial burden on the budgets of the healthcare providers. The aim of this book is to become a state-of-the-art reference, discussing progress made, as well as prompting future directions on theories, practices, standards, and strategies related to the ELE area. The book contains 12 chapters and can serve as a valuable reference for undergraduate students, post-graduate students, educators, faculty members, researchers, engineers, medical doctors, healthcare organizations, insurance companies, and research strategists working in this area

RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Smart aging : utilisation of machine learning and the Internet of Things for independent living

Smart aging utilises innovative approaches and technology to improve older adults’ quality of life, increasing their prospects of living independently. One of the major concerns the older adults to live independently is “serious fall”, as almost a third of people aged over 65 having a fall each year. Dementia, affecting nearly 9% of the same age group, poses another significant issue that needs to be identified as early as possible. Existing fall detection systems from the wearable sensors generate many false alarms; hence, a more accurate and secure system is necessary. Furthermore, there is a considerable gap to identify the onset of cognitive impairment using remote monitoring for self-assisted seniors living in their residences. Applying biometric security improves older adults’ confidence in using IoT and makes it easier for them to benefit from smart aging. Several publicly available datasets are pre-processed to extract distinctive features to address fall detection shortcomings, identify the onset of dementia system, and enable biometric security to wearable sensors. These key features are used with novel machine learning algorithms to train models for the fall detection system, identifying the onset of dementia system, and biometric authentication system. Applying a quantitative approach, these models are tested and analysed from the test dataset. The fall detection approach proposed in this work, in multimodal mode, can achieve an accuracy of 99% to detect a fall. Additionally, using 13 selected features, a system for detecting early signs of dementia is developed. This system has achieved an accuracy rate of 93% to identify a cognitive decline in the older adult, using only some selected aspects of their daily activities. Furthermore, the ML-based biometric authentication system uses physiological signals, such as ECG and Photoplethysmogram, in a fusion mode to identify and authenticate a person, resulting in enhancement of their privacy and security in a smart aging environment. The benefits offered by the fall detection system, early detection and identifying the signs of dementia, and the biometric authentication system, can improve the quality of life for the seniors who prefer to live independently or by themselves