This paper proposes to design, develop and implement a fast and markerless mobile augmented reality system to achieve the registration for, the visualization of, and the interaction with machines in indoor smart factories with Industry 4.0 vision. A lightweight deep-learning image detection module based on MobileNets running on mobile devices is used to detect/recognize different machines and different portions of machines. Internet of Things (IoT) networking allows machines and sensors in machines to report data, such as machine settings and machine states, to the cloud-side server. Thus, augmented information associated with a machine portion can be derived from the server and superimposed with the portion image shown on the device display. Furthermore, interaction methods based on touch gestures and distance calculation are also implemented. A prototype system is developed and tested in a mechanical workshop for the purpose of validation and evaluation. The system is shown to achieve high detection accuracy, intuitive visualization, and unique interaction modes.

Indoor Augmented Reality Using Deep Learning for Industry 4.0 Smart Factories

Real time performance analysis of secure IoT protocols for microgrid communication

In this article. the authors present a review on the IoT (Internet of Things) and its future scope in various areas. The IoT is one of the latest systems which provide a set of new services for upcoming technological innovations. It is said to be integration of cyber world with the physical world and empowered by the development of RFID, smart sensors, communication technology and internet protocols. The most important application of IoT is to deliver a class of application directly through smart sensors. Exponential development in mobile technology and machine to machine technologies has been done through the IoT only. In the near future, the IoT will be solely responsible for smart decision making and this will be implemented by incorporating new technologies with smart physical objects. Despite all these advancements by researchers, standardization bodies, industries, alliances and others there are still some problems while using IoT.

A Survey on IoT (Internet of Things) Emerging Technologies and Its Application

In-network middleboxes are vital for the Internet-of-Things (IoT) system security, but the widely adopted transport layer security (TLS) protocol blinds application-level middleboxes due to the encryption of traffic data. To resolve this problem, many solutions have been proposed to date. Among them, SplitTLS is widely adopted in the industry by proxy manufacturers. It requires TLS client to install customized root certificates and incurs additional security flaws, e.g., disabling server authentication and using weak cipher suites. Another approach is to customize the TLS protocol where middleboxes are enabled via either performing handshake directly with TLS endpoints or receiving session key materials in an out-of-band manner. Overall, current solutions would either jeopardize the original TLS handshake procedure or incur additional overheads on the endpoints. In this article, we design a new middlebox-enhanced TLS (ME-TLS), which enables endpoints to introduce authenticated middleboxes into a TLS session while control middleboxes’ access permission and processing order of traffic data. Particularly, in our proposed ME-TLS, the handshake structure of TLS keeps unchanged and middleboxes work in a passive manner. That is, middleboxes in the ME-TLS could recover session key materials by monitoring handshake messages passively instead of interacting with endpoints; secondary secure channels for key transmission are also not needed in our ME-TLS. We implement our ME-TLS based on the TLS 1.3 protocol and evaluate its performances. The experimental results demonstrate that our proposal is practical and deployable for real-world IoT scenarios.

ME-TLS: Middlebox-Enhanced TLS for Internet-of-Things Devices

Process monitoring at industrial sites contributes to system stability by detecting and diagnosing unexpected changes in a system. Today, as the infrastructure of industrial sites is advancing because of the development of communication technology, vast amounts of data are generated, and the importance of a way to effectively monitor such data in order to diagnose a system is increasing daily. Because a method based on a deep neural network can effectively extract information from a large amount of data, methods have been proposed to monitor processes using such networks to detect system faults and abnormalities. Neural-network-based process monitoring is effective in detecting faults, but has difficulty in diagnosing because of the limitations of the black-box model. Therefore, in this paper we propose a process-monitoring framework that can detect and diagnose faults. The proposed method uses a class activation map that results from diagnosis of faults and abnormalities, and verifies the diagnosis by post-processing the class activation map. This improves the detection of faults and abnormalities and generates a class activation map that provides a more verified diagnosis to the end user. In order to evaluate the performance of the proposed method, we did a simulation using publicly available industrial motor datasets. In addition, after establishing a system that can apply the proposed method to actual manufacturing companies that produce sapphire nozzles, we carried out a case study on whether fault detection and diagnosis were possible.

https://www.mdpi.com/1424-8220/20/23/6858/pdf

VODCA: Verification of Diagnosis Using CAM-Based Approach for Explainable Process Monitoring

Internet of things refers to uniquely identifiable objects and the representation of these physical objects in a virtual form in an Internet like structure. The number of things that get added to the network are increasing day by day. These connected devices are bound to reach 50 billion by 2020. MQTT or Message Queue Telemetry Transport is an Internet Of Things protocol for machine to machine communication. The protocol was invented by Andy Stanford-Clark of IBM, and Arlen Nipper of Cirrus Link Solution. MQTT is a Client Server publish/subscribe messaging transport protocol. It is light weight, open, simple, and designed so as to be easy to implement. These paper is designed to introduced the fundamental information about MQTT protocol. It represents an overview of MQTT from starting history till the present development.
Keywords- MQTT; IoT; publish/subscribe; MQTT-SN.

Pooja A. Nimkar

Papers

MQTT-Message Queuing Telemetry Transport protocol