Building a National IoT Plan: Policy Recommendations and the Case of Brazil

The Internet of Things (“IoT”) is an expression that refers to a whole set of new services and devices that includes at least three fundamental aspects: connectivity, use of sensors or actuators, and computational capacity for data processing and storage. The Internet of Things goes beyond connecting objects to each other; it also gives them the power to process data (thereby making them "smart"). For developing countries such as Brazil, the opportunities offered by the Internet of Things can compensate for shortcomings in infrastructure and services, and can improve innovation, quality of life, productivity, and even the economic complexity of our basket of export products. However, the way in which each country will seize this opportunity will depend on its specific aspirations and strategies. The broader economic, social, political, and legal context of the country should be considered, as well as the local development of information and communication technologies. For this reason, the National Bank for Economic and Social Development (BNDES), in partnership with the Ministry of Science, Technology, Innovation and Communications (MCTIC), has commissioned this study, "Internet of Things: An Action Plan for Brazil." This study, mapped by a consortium comprised by McKinsey & Company, the CPqD Foundation, and Pereira Neto | Macedo Law Firm, outlines the local technological and economic challenges related to the topic, as well as well as how to address legal issues inherent to the development of IoT in Brazil

Research on Sensor Network Spectrum Detection Technology based on Cognitive Radio Network

With the bursting development of computer science and the hardware technology, Internet of Things and wireless sensor networks has been popularly studied in the community of engineering. Under the environment of Internet of Things, we carry out theoretical analysis and numerical simulation on the sensor network spectrum detection technology based on cognitive radio network. As a means of information and intelligence, information service system is an important research hotspot in the field of Internet of things. Wireless sensor network is composed of a large number of micro sensor nodes, which have the function of information collection, data processing, and wireless communication, characterized by the integration of wireless self-organization. However, most of the methodologies proposed by the other institutes are suffering form the high complexity while with the high time-consuming when processing information. Therefore, this study is to assess the economic feasibility of using the optimized multipath protocol availability and the increased bandwidth and several mobile operators through the use of cost-benefit analysis, single path selection model is to develop more path agreement to achieve better performance. To test the robustness, we compare our method with the other state-of-the-art approach in the simulation section and proves the effectiveness of our methodology. The experimental result reflected that our approach could achieve higher accuracy with low time-consuming when dealing with complex sources of information

DNA Encoded Elliptic Curve Cryptography System for IoT Security

In the field of Computer Science and Information Technology Internet of Things (IoT) is one of the emerging technologies. In IoT environment several devices are interconnected and transmit data among them. There may be some security vulnerability arise within the IoT environment. Till date, IoT has not been widely accepted due to its security flaws. Hence to keep the IoT environment most robust, we propose a stable security framework of IoT with Elliptic Curve Cryptography (ECC) using DNA Encoding. The ECC is most lightweight cryptography technique among other well known public key cryptography techniques. To increase encryption complexity, DNA encoding mechanism of DNA computing with ECC is preceded

From mechatronics to the Cloud

At its conception mechatronics was viewed purely in terms of the ability to integrate the technologies of mechanical and electrical engineering with computer science to transfer functionality, and hence complexity, from the mechanical domain to the software domain. However, as technologies, and in particular computing technologies, have evolved so the nature of mechatronics has changed from being purely associated with essentially stand-alone systems such as robots to providing the smart objects and systems which are the building blocks for Cyber-Physical Systems, and hence for Internet of Things and Cloud-based systems. With the possible advent of a 4th Industrial Revolution structured around these systems level concepts, mechatronics must again adapt its world view, if not its underlying technologies, to meet this new challenge

A Novel Shortcut Addition Algorithm With Particle Swarm for Multisink Internet of Things

[EN] The Internet of Things integrates a large number of distributed nodes to collect or transmit data. When the network scale increases, individuals use multiple sink nodes to construct the network. This increases the complexity of the network and leads to significant challenges in terms of the existing methods with respect to the aspect of data forwarding and collection. In order to address the issue, this paper proposes a Shortcut Addition strategy based on the Particle Swarm algorithm (SAPS) for multisink network. It constructs a network topology with multiple sinks based on a small-world network. In the SAPS, we create a fitness function by combining the average path length and load of the sink node, to evaluate the quality of a particle. Subsequently, crossover and mutation are used to update the particles to determine the optimal solution. The simulation results indicate that the SAPS is superior both to the greedy model with small world and the load-balanced multigateway aware long link addition strategy in terms of the average path length, load balance, and number of added shortcuts.This work was supported by the National Natural Science Foundation of China under Grant 61672131 and Grant 61702365. Paper no. TII-19-0511.Qiu, T.; Li, B.; Zhou, X.; Song, H.; Lee, I.; Lloret, J. (2020). A Novel Shortcut Addition Algorithm With Particle Swarm for Multisink Internet of Things. IEEE Transactions on Industrial Informatics. 16(5):3566-3577. https://doi.org/10.1109/TII.2019.29250233566357716

Designing with the use of data for a better understanding of people and operating contexts in sociotechnical systems

The complex systems defined as ‘sociotechnical systems’ are made of software, hardware and people, somehow linked to the policy and a large number of stakeholders. They show complex dependencies and functional-based constraints. Over the last decades, the need to cope with the complexity took different forms, evolving in research activities and new disciplines. Systemic Design (SD) is an approach to manage the complexity that draws its origins into the General System Theories, cybernetics and generative science of the twentieth century, up to the recent attention towards systems thinking. Cyber-physical systems (CPSs), on the other hand, draws its origins from software and mechanical engineering, merging theory of cybernetics, mechatronics, design and process science. In CPS computing and communication are tightly coupled with the monitoring and control of entities in the physical world (Cheng and Atlee, 2008). The idea behind CPS is similar to the idea of the Internet of Things (IoT), with which it shares the same architecture. IoT is growing importance also in the design field. As design research by definition is intended to produce knowledge, this knowledge can be acquired by merging different methods, e.g. qualitative and quantitative. The data collected and made available from IoT technologies quantifies aspects that were not measurable before, providing content for other research activities such as ethnographic research and participatory activities. The designer could query some physical object and obtain useful data for the design. In this paper, we seek to address the design process in the era of the IoT, exploring the use of data in the early design stages as a means to investigate the application domain and stakeholders’ interaction with products

Security & Privacy Issues of Big Data in IOT based Healthcare System using Cloud Computing

The increasing popularity of IOT based technology in healthcare arena using cloud computing immensely emphasizes on using big data as a service for facilitating a proper structure for collected healthcare data and accommodating such ample number of diverse data for better diagnosis, medication and prediction of human health. The recent revolution brought in healthcare by internet of things allows us to experience the gigantic figure of data with more complexity, diversity and timeliness. Hence, the question rises in the researcher’s den about the security and privacy of such enormous data. Therefore, nowadays the limelight has been shifted questioning on how much secure and private those data which are generated from IOT devices and being stored in cloud environment? In this paper we have drafted a survey on most probable security as well as privacy problems related to healthcare which needs to grab the attention for enabling the healthcare system more reliable, more effective in terms of advancement of medical science and curing more patients at a time predicting the possible diseases