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

UAV-Assisted Sensor Data Dissemination in mmWave Vehicular Networks Based on Network Coding

Due to good maneuverability, UAVs and vehicles are often used for environment perception in smart cities. In order to improve the efficiency of sensor data sharing in UAV-assisted mmWave vehicular network (VN), this paper proposes a sensor data sharing method based on blockage effect identification and network coding. The concurrent sending vehicles selection method is proposed based on the availability of mmWave link, the number of target vehicles of sensor data packet, the distance between a sensor data packet and target vehicle, the number of concurrent sending vehicles, and the waiting time of sensor data packet. The construction method of the coded packet is put forward based on the status information about the existing packets of vehicles. Simulation results demonstrated that efficiency of the proposed method is superior to baseline solutions in terms of the packet loss ratio, transmission time, and packet dissemination ratio

Challenges and opportunities of introducing Internet of Things and Artificial Intelligence applications into Supply Chain Management

The study examines the challenges and opportunities of introducing Artificial Intelligence (AI) and the Internet of Things (IoT) into the Supply Chain Management (SCM). This research focuses on the Logistic Management. The central research question is “What are the key challenges and opportunities of introducing AI and IoT applications into the Supply Chain Management?” The goal of this research is to collect the most appropriate literature to help create a conceptual framework, which involves the integration of the IoT and AI applications into contemporary supply chain management with the emphasis on the logistics management. Additionally, the role of 5G Network is closely studied in order to indicate its capabilities and the processing capacity that it can provide to the AI and IoT operations. In addition, the semi-structured online interview with the top managers from several companies was conducted in order to identify the degree of readiness of the companies for the AI and IoT applications in SCM. From the retrieved results, the major challenges of integrating the IoT into SCM are the security and privacy issues, the sensitivity of the data and high costs of the implementation at an initial stage. Moreover, the research results have shown that the IoT applications can positively affect the SCM activities, in particular, the high visibility across the SC, an effective traceability and an automated data collection. Furthermore, the predictive analysis of AI programs can help the SCM to eliminate the potential errors and failures in the processes.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

DESIGN FRAMEWORK FOR INTERNET OF THINGS BASED NEXT GENERATION VIDEO SURVEILLANCE

Modern artificial intelligence and machine learning opens up new era towards video surveillance system. Next generation video surveillance in Internet of Things (IoT) environment is an emerging research area because of high bandwidth, big-data generation, resource constraint video surveillance node, high energy consumption for real time applications. In this thesis, various opportunities and functional requirements that next generation video surveillance system should achieve with the power of video analytics, artificial intelligence and machine learning are discussed. This thesis also proposes a new video surveillance system architecture introducing fog computing towards IoT based system and contributes the facilities and benefits of proposed system which can meet the forthcoming requirements of surveillance. Different challenges and issues faced for video surveillance in IoT environment and evaluate fog-cloud integrated architecture to penetrate and eliminate those issues. The focus of this thesis is to evaluate the IoT based video surveillance system. To this end, two case studies were performed to penetrate values towards energy and bandwidth efficient video surveillance system. In one case study, an IoT-based power efficient color frame transmission and generation algorithm for video surveillance application is presented. The conventional way is to transmit all R, G and B components of all frames. Using proposed technique, instead of sending all components, first one color frame is sent followed by a series of gray-scale frames. After a certain number of gray-scale frames, another color frame is sent followed by the same number of gray-scale frames. This process is repeated for video surveillance system. In the decoder, color information is formulated from the color frame and then used to colorize the gray-scale frames. In another case study, a bandwidth efficient and low complexity frame reproduction technique that is also applicable in IoT based video surveillance application is presented. Using the second technique, only the pixel intensity that differs heavily comparing to previous frame’s corresponding pixel is sent. If the pixel intensity is similar or near similar comparing to the previous frame, the information is not transferred. With this objective, the bit stream is created for every frame with a predefined protocol. In cloud side, the frame information can be reproduced by implementing the reverse protocol from the bit stream. Experimental results of the two case studies show that the IoT-based proposed approach gives better results than traditional techniques in terms of both energy efficiency and quality of the video, and therefore, can enable sensor nodes in IoT to perform more operations with energy constraints

Smart ports: towards a high performance, increased productivity, and a better environment

Ports are currently competing fiercely for capital and global investments in order to improve revenues, mostly by improving performance and lowering labor costs. Smart ports are a fantastic approach to realize these elements since they integrate information and communication technologies within smart applications, ultimately contributing to port management improvement. This leads to greater performance and lower operational expenses. As a result, several ports in Europe, Asia, Australia, and North America have gone smart. However, there are a lot of critical factors to consider when automating port operations, such as greenhouse gas emissions, which have reached alarming proportions. The purpose of this study is to define the most essential tasks conducted by smart ports, such as the smart ship industry, smart gantry and quayside container cranes, transport automation, smart containers, and energy efficiency. Furthermore, it gives a model of the smart port concept and highlights the critical current technologies on which the ports are based. Each technology’s most significant contributions to its development are noted. This technology is compared to more traditional technologies. It is hoped that this effort would pique the curiosity of fresh researchers in this sector

Review. Monitoring the intermodal, refrigerated transport of fruit using sensor networks

Most of the fruit in Europe is transported by road, but the saturation of the major arteries, the increased demand for freight transport, and environmental concerns all indicate there is a need to change this means of transport. A combination of transport modes using universal containers is one of the solutions proposed: this is known as intermodal transport. Tracking the transport of fruit in reefer containers along the supply chain is the means by which product quality can be guaranteed. The integration of emerging information technologies can now provide real-time status updates. This paper reviews the literature and the latest technologies in this area as part of a national project. Particular emphasis is placed on multiplexed digital communication technologies and wireless sensor networks