Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Distributed communications and control network for robotic mining

The application of robotics to coal mining machines is one approach pursued to increase productivity while providing enhanced safety for the coal miner. Toward that end, a network composed of microcontrollers, computers, expert systems, real time operating systems, and a variety of program languages are being integrated that will act as the backbone for intelligent machine operation. Actual mining machines, including a few customized ones, have been given telerobotic semiautonomous capabilities by applying the described network. Control devices, intelligent sensors and computers onboard these machines are showing promise of achieving improved mining productivity and safety benefits. Current research using these machines involves navigation, multiple machine interaction, machine diagnostics, mineral detection, and graphical machine representation. Guidance sensors and systems employed include: sonar, laser rangers, gyroscopes, magnetometers, clinometers, and accelerometers. Information on the network of hardware/software and its implementation on mining machines are presented. Anticipated coal production operations using the network are discussed. A parallelism is also drawn between the direction of present day underground coal mining research to how the lunar soil (regolith) may be mined. A conceptual lunar mining operation that employs a distributed communication and control network is detailed

Integration of the Alexa assistant as a voice interface for robotics platforms

Virtual assistants such as Cortana or Google Assistant are becoming familiar devices in everyday environments, where they are used to control real devices through natural language. This paper extends this application scenario, and it describes the use of the Alexa assistant from Amazon through an Echo dot device to drive the behaviour of a robotic platform. The paper focuses on the description of the technologies employed to set such ecosystem. Significantly, the proposed architecture is based, from the remote server to the on-board controllers, in LowEnergy (LE) hardware and a scalable software platform. This approach will ease programmers integrating different platforms, e.g. mobile-based applications to control robots or home-made devices.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Implementation of Bluetooth Enabled Home Automation System

Home automation is becoming more and more popular as a concept because it increases productivity by lowering human oversight and labor. Home automation systems allow us to operate a variety of gadgets, including air conditioners, TVs, fans, lights, and more. Furthermore, additional functions like emergency systems, security, alarms, etc. may be incorporated into home automation systems. There are numerous varieties of home automation technologies, including those that are controlled via Bluetooth, the Internet, RF, infrared, and other remotes. Each type comes with its own benefits and drawbacks. For this research, we have programmed and constructed a Bluetooth-controlled home automation device using a Bluetooth-enabled Android phone. The designed device is able to switch enabled home appliances within a 100-meter radius of the phone.&nbsp

Chapter BCI Integration: Application Interfaces

Natural disaster

socialAWARE:mobile wireless sensing network

Abstract. This thesis presents a software tool for Android smartphones called socialAWARE, a mobile wireless sensing network. socialAWARE uses zeroconf networking to discover other mobile devices and their connection information on a local area network. It uses built-in mobile sensors to collect data and transmit it in real time using CoAP’s machine-to-machine protocol. SocialAWARE aims at helping users to quickly deploy a wireless sensor network without an emphasis in configuration or technical background. socialAWARE is implemented as a plug-in for AWARE framework [1], which uses diverse protocols to enhance its capabilities. Together, socialAWARE plug-in and AWARE allows for data collection and real-time sharing of sensor data between different devices (LAMP server, smartwatch, Android, iOS). After the implementation of the plug-in, the performance of the protocols were evaluated by conducting several experiments. We also compare CoAP with MQTT with respect to their technical performance in terms of latency, throughput, and network usage. Based on the experimental results, we discuss the advantages and limitations of the system. Finally, we conclude this thesis by discussing a number of improvements for future iterations of socialAWARE, based on the literature survey and experiment results