scholarly journals Scientific Developments and New Technological Trajectories in Sensor Research

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7803
Author(s):  
Mario Coccia ◽  
Saeed Roshani ◽  
Melika Mosleh

Scientific developments and new technological trajectories in sensors play an important role in understanding technological and social change. The goal of this study is to develop a scientometric analysis (using scientific documents and patents) to explain the evolution of sensor research and new sensor technologies that are critical to science and society. Results suggest that new directions in sensor research are driving technological trajectories of wireless sensor networks, biosensors and wearable sensors. These findings can help scholars to clarify new paths of technological change in sensors and policymakers to allocate research funds towards research fields and sensor technologies that have a high potential of growth for generating a positive societal impact.

Author(s):  
Mario Coccia ◽  
Saeed Roshani ◽  
Melika Mosleh

The fundamental question in the field of sensor research is new directions of scientific fields, which play a vital role in the progress of science and technology. This study confronts this question here by developing a bibliometric analysis, which endeavors to explain the evolution of sensor research and new technologies that are critical to science and society. The database of Scopus concerning scientific documents and patents is used for statistical and computational analyses in these topics. Results suggest that emerging technological trajectories in sensors are wireless sensor networks, wearable sensors and biosensors. Main characteristics of these growing research fields and technologies in sensors are described for fruitful implications of research and innovation policy directed to science advances and technological change in society.


Author(s):  
Subharthi Banerjee ◽  
Michael Hempel ◽  
Hamid Sharif

Railroad environments are generally considered to be among the most dynamic workplace environments, even with constant improvement efforts by the railroad industry. While there has been great progress in equipment safety, personnel safety is a significantly harder challenge. These challenges are primarily derived from the presence of heavy moving machinery in close proximity to personnel and the difficulty of designing reliable wearable protection devices. Additionally, variable weather conditions, challenging walking conditions (ballast, trip hazards, etc.), and difficulty to focus on environment, moving objects, and on tasks at hand place the employees in constant peril. Therefore, our survey is focused on exploring solutions for protecting employees through unified system modeling and design that makes the employee integral to the process and results in personal protective devices that work with the environment and the employee, not against them. The optimal system design integrates not only protection of the employees from falls, unsafe practices, or collisions, but also aids in resource planning, safe operation and accounting of “near-miss” situations. In recent years the railroads have made significant investments in process automation and monitoring solutions such as Wireless Sensor Networks. These technologies are becoming increasingly cloud-connected and autonomous. They provide a plethora of information about equipment positions, movement, railcar lading, and many other factors, all of which are highly useful in the design and implementation of a railyard worker protection system. They allow us to predict position and movement, and can thus be used to provide effective proximity detection and alerting in some railyard regions where these systems are installed. Additionally, we discuss several technologies addressing near-collision, fall, and proximity situations through RF and non-RF-based techniques. The railroad industry has been advancing efforts leveraging these technologies to improve the safety of their workers. However, there are also many challenges that remain largely unaddressed. For example, in railroads, a detailed and exhaustive causation analysis for worker incidents has yet to be conducted. Therefore, in an environment like a railyard there is no solution to detect or prevent Employee on Duty (EOD) fall, collision, or health issues such as dehydration, psychological issues and high blood pressure. Protective devices worn by workers is believed to be one of the most important, cost-effective, and scalable potential candidate solutions. Recent advances are making wearable wireless body area networks (WBAN) and wireless sensor networks (WSNs) that are distributed and large-scale a reality. Such distributed networks consist of wearable sensors, fixed-installation sensors and communication links between all of them. The challenges are found in selecting wearable sensors, researching reliable communication among nodes without interfering with proximity detection and suitable for high-multipath, non-line of sight channel conditions, wearable antenna designs, power supply requirements, etc. A dense, distributed, large-scale environment like a railyard requires comprehensive workspace modelling and safety analysis. Interference related to RF sensor deployment, blind spots in vision-based approaches, and wireless propagation in intra and inter-WBAN communication due to dense non-Line-of-Sight workspace environments, metallic heavy machinery and the use of RF sensors, are all individual research challenges in this domain. This paper reviews these challenges, explores potential solutions, and thus provides a comprehensive survey of a holistic system design approach for a wearable railyard worker protection system that is unobtrusive, effective, and reliable.


Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3446
Author(s):  
Adrià Mallorquí ◽  
Agustín Zaballos

Antarctica is a key location for many research fields. The lack of telecommunication systems that interconnect remote base camps hardens the possibility of building synergies among different polar research studies. This paper defines a network architecture to deploy a group of interconnected remote Antarctic wireless sensor networks providing an IoT telemetry service. Long backhaul NVIS links were used to interconnect remote networks. This architecture presents some properties from challenging networks that require evaluating the viability of the solution. A heterogeneous layer-based model to measure and improve the trustworthiness of the service was defined and presented. The model was validated and the trustworthiness of the system was measured using the Riverbed Model simulator.


2021 ◽  
Author(s):  
Mario Coccia

Abstract Quantum computer and computing are areas of theoretical and experimental research having a phase of growth that can generate a tectonic shift of the evolution of technology in society. The scientific and technological development in quantum research is due to a range of driving technological trajectories that are growing to solve more and more complex problems. The goal of this study is to detect emerging research fields and technological trajectories of quantum computing to explain and generalize, whenever possible, the technological characteristics of evolutionary dynamics in science and technology. Database of Scopus concerning documents and patents is used for statistical analyses to determine the growth of research fields and technological trajectories having a high potential impact in science and society. Results suggest that quantum research is driven by emerging scientific and technological trajectories given by Qubits, Quantum optics, Quantum circuit, Semiconductor quantum dots and quantum information. Overall, this study explains, whenever possible, emerging research fields and technological technologies in quantum computing that support scientific and technological change directed to future economic and social progress. Finally, technology analysis of this study can help policymakers to support the allocation of resources for all areas of Quantum Science having a high potential of growth and positive impact in science and society.


Author(s):  
Pratyay Kuila ◽  
Prasanta K. Jana

With proliferation of Computational Intelligence (CI), evolutionary algorithms have drawn enormous attention among researchers. Such algorithms have been studied to solve many optimization problems. Clustering and routing are two well known optimization problems which are well researched in the field of Wireless Sensor Networks (WSNs). These problems are NP-hard. Therefore, many researchers have applied meta-heuristic approaches to develop various evolutionary algorithms to solve them. In this chapter, the authors rigorously study and present various evolutionary algorithms that include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution, etc. and show how these algorithms are applied to solve clustering and routing problems in WSNs. The chapter starts with an introduction of WSNs along with clustering and routing problems in WSNs accompanied by a discussion why these problems are solved by evolutionary algorithms. The authors then give an overview of various evolutionary approaches that are applied to solve clustering and routing problems. Various evolutionary algorithms are then presented towards the solution of these problems. A comparison table is also made by highlighting strengths and weaknesses of the algorithms. Finally, the authors present new directions of future research in this domain.


2020 ◽  
pp. 125-146 ◽  
Author(s):  
Pratyay Kuila ◽  
Prasanta K. Jana

With proliferation of Computational Intelligence (CI), evolutionary algorithms have drawn enormous attention among researchers. Such algorithms have been studied to solve many optimization problems. Clustering and routing are two well known optimization problems which are well researched in the field of Wireless Sensor Networks (WSNs). These problems are NP-hard. Therefore, many researchers have applied meta-heuristic approaches to develop various evolutionary algorithms to solve them. In this chapter, the authors rigorously study and present various evolutionary algorithms that include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution, etc. and show how these algorithms are applied to solve clustering and routing problems in WSNs. The chapter starts with an introduction of WSNs along with clustering and routing problems in WSNs accompanied by a discussion why these problems are solved by evolutionary algorithms. The authors then give an overview of various evolutionary approaches that are applied to solve clustering and routing problems. Various evolutionary algorithms are then presented towards the solution of these problems. A comparison table is also made by highlighting strengths and weaknesses of the algorithms. Finally, the authors present new directions of future research in this domain.


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