Data Mining - Concepts and Techniques.

A super-peer is a node in a peer-to-peer network that operates both as a server to a set of clients, and as an equal in a network of super-peers. Super-peer networks strike a balance between the efficiency of centralized search, and the autonomy, load balancing and robustness to attacks provided by distributed search. Furthermore, they take advantage of the heterogeneity of capabilities (e.g., bandwidth, processing power) across peers, which recent studies have shown to be enormous. Hence, new and old P2P systems like KaZaA and Gnutella are adopting super-peers in their design. Despite their growing popularity, the behavior of super-peer networks is not well understood. For example, what are the potential drawbacks of super-peer networks? How can super-peers be made more reliable? How many clients should a super-peer take on to maximize efficiency? we examine super-peer networks in detail, gaming an understanding of their fundamental characteristics and performance tradeoffs. We also present practical guidelines and a general procedure for the design of an efficient super-peer network.

Designing an Super-Peer Network

Network Simulator NS2

In this era of research and technology, Internet of things (IoT) takes a prominent part in the evolution of applications of the various field like health, education, smart cities, homes, agriculture etc. This paper provides a survey of the IoT ecosystem. All the components of IoT and their significance has been elaborated. The smart sensors collaborate through wireless communication and internet, with zero human activity, to deliver automated intelligent applications. In this internet world, machine-to-machine (M2M) technologies are the first phase of the IoT. As IoT is expanding, it is bringing together vast technologies as in Big Data, Artificial Intelligent, Machine Learning to tackle the huge data and devices. This paper starts by providing an overview of the taxonomy of the IoT ecosystem. Then, it provides a technical overview of IoT enabling architectures, devices, gateways, operating systems (OS), middleware, platforms, data storage, security, communication protocols and interfaces for the data flow in an ecosystem. This paper also discusses the key hurdles that need to be tackled for expanding IoT. A relation between IoT and new technologies like big data, cloud and fog computing has been briefed. Finally, it presents the growing applications that IoT delivers.

IoT Ecosystem: A Survey on Devices, Gateways, Operating Systems, Middleware and Communication

JackIn is a new human-human communication framework for connecting two or more people. With first-person view video streaming from a person (called Body) wearing a transparent head-mounted display and a head-mounted camera, the other person (called Ghost) participates in the shared first-person view. With JackIn, people's activities can be shared and assistance or guidance can be given through other peoples expertise. This can be applied to daily activities such as cooking lessons, shopping navigation, education in craft-work or electrical work, and sharing experiences of sporting and live events. For a better viewing experience with frist-person view, we developed the out-of-body view in which first-person images are integrated to construct a scene around a Body, and a Ghost can virtually control the viewpoint to look around the space surrounding the Body. We also developed a tele-pointing gesture interface. We conducted an experiment to evaluate how effective this framework is and found that Ghosts can understand the spatial situation of the Body.

JackIn: Integrating first-person view with out-of-body vision generation for human-human augmentation

Frequent and accurate inspections of industrial components and equipment are essential because failures can cause unscheduled downtimes, massive material, and financial losses or even endanger workers. In the mining industry, belt idlers or rollers are examples of such critical components. Although there are many precise laboratory techniques to assess the condition of a roller, companies still have trouble implementing a reliable and scalable procedure to inspect their field assets. This article enumerates and discusses the existing roller inspection techniques and presents a novel approach based on an Unmanned Aerial Vehicle (UAV) integrated with a thermal imaging camera. Our preliminary results indicate that using a signal processing technique, we are able to identify roller failures automatically. We also proposed and implemented a back-end platform that enables field and cloud connectivity with enterprise systems. Finally, we have also cataloged the anomalies detected during the extensive field tests in order to build a structured dataset that will allow for future experimentation.

https://www.mdpi.com/1424-8220/20/8/2243/pdf

A UAV-Based Framework for Semi-Automated Thermographic Inspection of Belt Conveyors in the Mining Industry.

Wearable devices have emerged in the last years with new applications that provide user convenience. Healthcare, sports, safety are some examples of applications embedded in thousands of devices released in the last years. Wearable operating systems with different focus emerged together with wearable applications in order to make adjustments and optimizations of software and hardware. This paper presents a wearable operating systems discussion and shows the current challenges and wearable operating system inuence. We developed a wearable appliance for geology. The wearable contains a Head Mounted Display (HMD) assembled with Google Cardboard API and sensors connected to developments boards. For each system component was used different operating systems according to hardware and software available. The results indicate some trends for wearable operating systems.

Building Wearables for Geology: An Operating System Approach

One of the most critical equipment used by mining companies is the belt conveyor. Thousands of kilometers of these elements are used for bulk material transportation. A belt conveyor system is composed of several components, and the maintenance process is not trivial and usually reactive. Thousands of dollars are lost per hour with the failure of a conveyor belt system. This occurs due to the lack of appropriate mechanisms for efficient monitoring and integration of this process to the enterprise systems. This paper presents a novel monitoring and integration architecture for a Brazilian mining company. The challenge is to provide a mobile control system and its integration with the current enterprise solutions. We also describe a set of restrictions for the particular component (rollers) in order to identify methods for the integration. Preliminary results demonstrate our solution is a feasible alternative for the case study.

An Integrated Inspection System for Belt Conveyor Rollers - Advancing in an Enterprise Architecture.

Ecological environments research helps to assess the impacts on forests and managing forests. The usage of novel software and hardware technologies enforces the solution of tasks related to this problem. In addition, the lack of connectivity for large data throughput raises the demand for edge-computing-based solutions towards this goal. Therefore, in this work, we evaluate the opportunity of using a Wearable edge AI concept in a forest environment. For this matter, we propose a new approach to the hardware/software co-design process. We also address the possibility of creating wearable edge AI, where the wireless personal and body area networks are platforms for building applications using edge AI. Finally, we evaluate a case study to test the possibility of performing an edge AI task in a wearable-based environment. Thus, in this work, we evaluate the system to achieve the desired task, the hardware resource and performance, and the network latency associated with each part of the process. Through this work, we validated both the design pattern review and case study. In the case study, the developed algorithms could classify diseased leaves with a circa 90% accuracy with the proposed technique in the field. This results can be reviewed in the laboratory with more modern models that reached up to 96% global accuracy. The system could also perform the desired tasks with a quality factor of 0.95, considering the usage of three devices. Finally, it detected a disease epicenter with an offset of circa 0.5 m in a 6 m × 6 m × 12 m space. These results enforce the usage of the proposed methods in the targeted environment and the proposed changes in the co-design pattern.

Wearable Edge AI Applications for Ecological Environments.

Wearable devices have increasingly become popular in recent years. Devices attached to users body now remotely monitor his daily activities/health. However, some operating systems running on these devices were not initially designed and developed for this purpose, letting them have a poor performance or even requiring to spend more resources or better hardware. This work presents a comparison, driven by specific constraints, between operating systems for wearable devices. Our research raised the key constraints of this context and figured out which operating system has the best performance. Results presented here shows that evaluated operating systems do not have enough performance when considering wearable devices specific constraints, letting us conclude that improvements should be made.

Saul Delabrida

Papers

A UAV-Based Framework for Semi-Automated Thermographic Inspection of Belt Conveyors in the Mining Industry.

Building Wearables for Geology: An Operating System Approach

An Integrated Inspection System for Belt Conveyor Rollers - Advancing in an Enterprise Architecture.

Wearable Edge AI Applications for Ecological Environments.

A Constraint-Driven Assessment of Operating Systems for Wearable Devices