Bibliometric analysis is growing research filed supported in different tools. Some of these tools are based on network representation or thematic analysis. Despite years of tools development, still, there is the need to support merging information from different sources and enhancing longitudinal temporal analysis as part of trending topic evolution. We carried out a new scientometric open-source tool called ScientoPy and demonstrated it in a use case for the Internet of things topic. This tool contributes to merging problems from Scopus and Clarivate Web of Science sources, extracts and represents h-index for the analysis topic, and offers a set of possibilities for temporal analysis for authors, institutions, wildcards, and trending topics using four different visualizations options. This tool enables future bibliometric analysis in different emerging fields.

Abstract:Internet of Things (IoT) is connecting billions of devices to the Internet. These IoT devices chain sensing, computation, and communication techniques, which facilitates remote data collection and analysis. wireless sensor networks (WSN) connect sensing devices together on a local network, thereby eliminating wires, which generate a large number of samples, creating a big data challenge. This IoT paradigm has gained traction in recent years, yielding extensive research from an increasing variety of perspectives, including scientific reviews. These reviews cover surveys related to IoT vision, enabling technologies, applications, key features, co-word and cluster analysis, and future directions. Nevertheless, we lack an IoT scientometrics review that uses scientific databases to perform a quantitative analysis. This paper develops a scientometric review about IoT over a data set of 19,035 documents published over a period of 15 years (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) in two main scientific databases (Clarivate Web of Science and Scopus). A Python script called ScientoPy was developed to perform quantitative analysis of this data set. This provides insight into research trends by investigating a lead author's country affiliation, most published authors, top research applications, communication protocols, software processing, hardware, operating systems, and trending topics. Furthermore, we evaluate the top trending IoT topics and the popular hardware and software platforms that are used to research these trends.

Field Programmable Gate Array (FPGA) is a general purpose programmable logic device that can be configured by a customer after manufacturing to perform from a simple logic gate operations to complex systems on chip or even artificial intelligence systems. Scientific publications related to FPGA started in 1992 and, up to now, we found more than 70,000 documents in the two leading scientific databases (Scopus and Clarivative Web of Science). These publications show the vast range of applications based on FPGAs, from the new mechanism that enables the magnetic suspension system for the kilogram redefinition, to the Mars rovers’ navigation systems. This paper reviews the top FPGAs’ applications by a scientometric analysis in ScientoPy, covering publications related to FPGAs from 1992 to 2018. Here we found the top 150 applications that we divided into the following categories: digital control, communication interfaces, networking, computer security, cryptography techniques, machine learning, digital signal processing, image and video processing, big data, computer algorithms and other applications. Also, we present an evolution and trend analysis of the related applications.

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Radio frequency identification (RFID) is widely used in several contexts, such as logistics, supply chains, asset tracking, and health, among others, therefore drawing the attention of many researchers. This paper presents a review of the most cited topics regarding RFID focused on applications, security, and privacy. A total of 62,685 records were downloaded from the Web of Science (WoS) and Scopus core databases and processed, reconciling the datasets to remove duplicates, resulting in 40,677 unique elements. Fundamental indicators were extracted and are presented, such as the citation number, average growth rate, and average number of documents per year. We extracted the top topics and reviewed the relevant indicators using a free Python tool, ScientoPy. The results are discussed in the following sections: the first is the Applications Section, whose subsections are the Internet of Things (IoT), Supply Chain Management, Localization, Traceability, Logistics, Ubiquitous Computing, Healthcare, and Access Control; the second is the Security and Privacy section, whose subsections are Authentication, Privacy, and Ownership Transfer; finally, we present the Discussion section. This paper intends to provide the reader with a global view of the current status of trending RFID topics and present different analyses from different perspectives depending on motivations or background.

Coffee is one of the leading worldwide drinks; therefore, it represents highly valued trade. However, coffee is a complex food from sowing to harvesting, processing, packaging, selling and consuming, although coffee is important in most of its stages, no studies have analyzed the dynamics of global coffee research. This paper presents an analysis of the evolution of Coffee related international research. It is based on the renowned literature databases published by Scopus and Web of Science. The parameters studied included growth of publications, the main journals, countries, institutions, and an author keywords analysis according to their relationship with topics such as agronomy, health, economy, chemistry or biological compound, product and unclassified words. Interest in harvesting techniques and coffee side factors have been increasing through last years in an exponential trend. Producer and consumer countries have composed a synergy with their research interest, that allows stating an upcoming growing in techniques headed to the quality beverage. The contribution is to visualize state of the art in the area of coffee knowledge to generate trends for future research.

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Silk is known as the queen of textiles due to its softness, durability, and luster. This textile is obtained from cocoons spun by larvae known as the silkworm. The combined effect of both temperature and humidity, determines the satisfactory growth of the silkworms and the production of good quality cocoons. For that rea- son, we propose a new prototype for silkworm incubators that monitors environmental conditions, created with Raspberry Pi due to its capabilities, features, and low cost. The prototype monitors the temperature, humidity, and luminosity in a silkworm incubator. The monitoring data are collected and saved on file hosting service, Google Drive, for subsequent analysis. Preliminary tests were gathered using the silkworm incubator of University of Cauca, Colombia.