Sudeep Ghimire

IoT based situational awareness framework for real-time project management

Factories of the Future roadmap identifies that the major challenges manufacturing companies face today are the growing complexity of their processes, therefore affecting the overall process of decision making. Thus, it is a very important research area to integrate the evolving technologies in the domain of Internet of Things (IoT) into the applications used for project management. At the same time, to capture events on the shop-floor and determine the meaning of information about those perceived events would be an important aspect for making decisions in heterogeneous, highly dynamic environments. This research paper aims to provide a framework for efficient project management by reducing the time for decision-making based on IoT technologies. The goal is pursued by dynamically establishing situational awareness on the top of existing manufacturing processes. The proposed framework is validated in real industrial scenario by implementing a platform for efficient project management within the domain of construction industry.

Framework for inter-operative e-Procurement marketplace

Pre-award is an important phase of overall processes in e-Procurement. This research work is based on project VortalWay and IMAGINE which made an extensive study to address interoperability between e-procurement platforms. This paper aims at presenting a theoretical model and implementation strategy to connect independent procurement platforms to form a common e-marketplace with least possible efforts within the scope of the pre-award business process. This paper presents a formal framework for realization of inter-operative marketplaces for e-procurement platforms along with implementation of prototype application for easy flow of messages during various processes of pre-award phase.

Continuous Data Collection Framework for Manufacturing Industries

The combination of high-performance and quality with cost-effective productivity, realizing reconfigurable, adaptive and evolving factories leading to sustainable manufacturing industries is one of the emerging research challenges in the domain of Internet of Things. So, it is important to define strategies and technical solutions to allow manufacturing process to autonomously react to the changing factors. Continuous data collection from heterogeneous sources and infusion of such data into suitable processes to enable almost real-time reactive systems is emerging research domain. This research work provides a technical framework for continuous data collection in support of the supply network and manufacturing assets optimization based on collaborative production planning. This research work explores its connection to legacy systems, software components and hardware devices to provide information to the different data consumers. The most relevant achievement of this work is the framework to bridge differences among computing systems, devices and networks allowing uniformity for data access by application decoupling data consumers from data sources.

Toward a unified intercloud interoperability conceptual model for IaaS cloud service

The concept of interoperation between cloud providers is a recent research challenging objective. Current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability. The paper proposes a conceptual model for Intercloud Interoperability, to enable schedule dynamic operation for Infrastructure as a Service (IaaS) between different clouds. The paper is providing a better understanding of elaborates on the cloud computing architecture, appropriate metrics for Service Level Agreements (SLA) and Quality of Service (QoS) models that are required for seamless integration and interoperability between cloud environments. Then, a conceptual model for the Intercloud Interoperability Framework for Workload Migration is proposed. The novel component of the framework that provides interoperability is the Transformation Engine that maps workload between heterogeneous cloud providers, whilst Model Driven Architecture (MDA) is adopted as an applicable method for developing the Transformation Engine module.

IoT and Self-Driving Cars a Revolution Beyond the Automobile Industry

Transportation is a sector of activity in permanent change. From airplanes to cars, trains and boats all forms of transportation aim at meeting personal or business needs of displacement of persons and goods. Those needs include safety, reliability, on time with the best effectiveness, and finally, providing the best price. This paper aims at studying car transportation’s consequences regarding last developments that culminate in the self-driving cars. This study analyses the impact of such changes at social and industrial level, considering also the coexistence of traditional cars and self-driving cars in diverse aspects. The authors aim to establish a proficient debate on such important changes for the near future, to create awareness of the potential consequences of such societal and business revolution and generate some conclusions addressing these complex challenges for the years to come. This paper also issues some recommendations for the coexistence of self-driving, autonomous and traditional cars during the transitory period.Copyright

Brain Inspired Health Monitoring Supported by the Cloud

The health status of a person can be assessed by specialized professionals with the help of medical devices. The assessment, in real-time, would be useful as most of the times a person is not in presence of health professionals. But own assessment lacks precision and reaction time that could be risky in critical conditions. The pervasiveness of Internet connections and ubiquity of smart devices makes it possible to overcome that limitation. By using sensing capabilities of portable/wearable devices in conjunction with medical knowledge and clinical history it is possible to monitor a person’s health status in real-time with reaction mechanisms. The objective is to keep track of collected evidence, and relate with existing knowledge for better assessment. This paper proposes a framework, inspired by the brain and physiology, capturing real-time health related information, at a person’s location, submitting that to the cloud for reasoning and decision and triggers advice or request medical assistance.

Towards the Framework for the Design of Human Centric Internet of Things

The research and development of Internet of Things (IoT) paradigm, encompassing different related concepts and technologies, such as Cyber Physical Systems and Wireless Sensor Networks, is currently facing the challenges related to a lack of possibilities to de-verticalize the market of devices. These challenges were caused by incoherent development of the different standards, models and languages for the devices operations, hence dramatically reducing their capability to interoperate. It is our belief that these challenges can be overcome by the design in which the devices networks are functioning by following the principles of human communication. In this paper, we propose a framework to support Knowledge Management of a human-centric IoT, while considering the different enabling factors in anthropomorphic approach, such as awareness, perceptivity and physiological enrolment. This framework takes into account a new type of data, a sensorial physiological data that is assumed to enrich the expressivity of devices and thus, enable more accurate and complete perception of the signals, transmitted by the devices.Copyright