scholarly journals LoggerBIT: An Optimization of the OpenLog Board for Data Logging with Low Cost Hardware Platforms for Biomedical Applications

Author(s):  
Margarida Reis ◽  
Hugo Plácido da Silva
2021 ◽  
Vol 10 (1) ◽  
pp. 13
Author(s):  
Claudia Campolo ◽  
Giacomo Genovese ◽  
Antonio Iera ◽  
Antonella Molinaro

Several Internet of Things (IoT) applications are booming which rely on advanced artificial intelligence (AI) and, in particular, machine learning (ML) algorithms to assist the users and make decisions on their behalf in a large variety of contexts, such as smart homes, smart cities, smart factories. Although the traditional approach is to deploy such compute-intensive algorithms into the centralized cloud, the recent proliferation of low-cost, AI-powered microcontrollers and consumer devices paves the way for having the intelligence pervasively spread along the cloud-to-things continuum. The take off of such a promising vision may be hurdled by the resource constraints of IoT devices and by the heterogeneity of (mostly proprietary) AI-embedded software and hardware platforms. In this paper, we propose a solution for the AI distributed deployment at the deep edge, which lays its foundation in the IoT virtualization concept. We design a virtualization layer hosted at the network edge that is in charge of the semantic description of AI-embedded IoT devices, and, hence, it can expose as well as augment their cognitive capabilities in order to feed intelligent IoT applications. The proposal has been mainly devised with the twofold aim of (i) relieving the pressure on constrained devices that are solicited by multiple parties interested in accessing their generated data and inference, and (ii) and targeting interoperability among AI-powered platforms. A Proof-of-Concept (PoC) is provided to showcase the viability and advantages of the proposed solution.


Molecules ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 49
Author(s):  
Hélida Gomes de Oliveira Barud ◽  
Robson Rosa da Silva ◽  
Marco Antonio Costa Borges ◽  
Guillermo Raul Castro ◽  
Sidney José Lima Ribeiro ◽  
...  

Bacterial cellulose (BC) is a natural polymer that has fascinating attributes, such as biocompatibility, low cost, and ease of processing, being considered a very interesting biomaterial due to its options for moldability and combination. Thus, BC-based compounds (for example, BC/collagen, BC/gelatin, BC/fibroin, BC/chitosan, etc.) have improved properties and/or functionality, allowing for various biomedical applications, such as artificial blood vessels and microvessels, artificial skin, and wounds dressing among others. Despite the wide applicability in biomedicine and tissue engineering, there is a lack of updated scientific reports on applications related to dentistry, since BC has great potential for this. It has been used mainly in the regeneration of periodontal tissue, surgical dressings, intraoral wounds, and also in the regeneration of pulp tissue. This review describes the properties and advantages of some BC studies focused on dental and oral applications, including the design of implants, scaffolds, and wound-dressing materials, as well as carriers for drug delivery in dentistry. Aligned to the current trends and biotechnology evolutions, BC-based nanocomposites offer a great field to be explored and other novel features can be expected in relation to oral and bone tissue repair in the near future.


Author(s):  
Stewart Smith ◽  
Hancong Wu ◽  
Jiabin Jia

This poster reports the design, implementation and testing of a portable and inexpensive bio-impedance measurement system intended for electrical impedance tomography (EIT) in cell cultures. The system is based on the AD5933 impedance analyser integrated circuit with additional circuitry to enable four-terminal measurement. Initial results of impedance measurements are reported along with an EIT image reconstructed using the open source EIDORS package.


2021 ◽  
Author(s):  
Rahat Nawaz ◽  
Sayed Tayyab Raza Naqvi ◽  
Batool Fatima ◽  
Nazia Zulfiqar ◽  
Muhammad Umer Farooq ◽  
...  

Abstract Nonwoven cotton fabric has been fabricated and designed for antibacterial applications using low cost and ecofriendly precursors. The treatment of fabric with alkali leads to formation of active sites. The surfaces were dip coated with silver nanaoparticles and chitosan. The surface was chlorinated in next step to transform amide (N-H) groups in chitosan into N-halamine (N-Cl). The modified and unmodified surfaces of the nonwoven cotton fabric have been characterized by FTIR, SEM, and XRD. The active chlorine loading is measured with iodine/ sodium thiosulphate. The antimicrobial activity and cell toxicity assay were carried out with and without modifications of nonwoven cotton fabric. The antimicrobial efficacies of loaded fabric were evaluated against four bacterial species (Micrococcus lutes, Staphylococcus aurea, Enterobacter aerogenes, and E.coli). It was found that modified fabric exhibited superior efficiency against gram-positive and gram-negative bacterial strains as compared to their bulk counterparts upon exposure without destroying and affecting fabric nature. The overall process is economical for commercial purposes. The modified fabric can be used for antimicrobial, health, and food packaging industries, and in other biomedical applications.


2018 ◽  
Vol 10 (38) ◽  
pp. 4648-4654 ◽  
Author(s):  
Tae Joon Kwak ◽  
Wookkun Kwon ◽  
Jiang Yang ◽  
Sang Woo Lee ◽  
Woo-Jin Chang

Paper fluidics has recently offered an approach to precisely guide liquid flow in analytical devices with a low-cost regime.


Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 404 ◽  
Author(s):  
Daniel Costa ◽  
Cristian Duran-Faundez

With the increasing availability of affordable open-source embedded hardware platforms, the development of low-cost programmable devices for uncountable tasks has accelerated in recent years. In this sense, the large development community that is being created around popular platforms is also contributing to the construction of Internet of Things applications, which can ultimately support the maturation of the smart-cities era. Popular platforms such as Raspberry Pi, BeagleBoard and Arduino come as single-board open-source platforms that have enough computational power for different types of smart-city applications, while keeping affordable prices and encompassing many programming libraries and useful hardware extensions. As a result, smart-city solutions based on such platforms are becoming common and the surveying of recent research in this area can support a better understanding of this scenario, as presented in this article. Moreover, discussions about the continuous developments in these platforms can also indicate promising perspectives when using these boards as key elements to build smart cities.


Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3055
Author(s):  
Olivier Pieters ◽  
Tom De Swaef ◽  
Peter Lootens ◽  
Michiel Stock ◽  
Isabel Roldán-Ruiz ◽  
...  

The study of the dynamic responses of plants to short-term environmental changes is becoming increasingly important in basic plant science, phenotyping, breeding, crop management, and modelling. These short-term variations are crucial in plant adaptation to new environments and, consequently, in plant fitness and productivity. Scalable, versatile, accurate, and low-cost data-logging solutions are necessary to advance these fields and complement existing sensing platforms such as high-throughput phenotyping. However, current data logging and sensing platforms do not meet the requirements to monitor these responses. Therefore, a new modular data logging platform was designed, named Gloxinia. Different sensor boards are interconnected depending upon the needs, with the potential to scale to hundreds of sensors in a distributed sensor system. To demonstrate the architecture, two sensor boards were designed—one for single-ended measurements and one for lock-in amplifier based measurements, named Sylvatica and Planalta, respectively. To evaluate the performance of the system in small setups, a small-scale trial was conducted in a growth chamber. Expected plant dynamics were successfully captured, indicating proper operation of the system. Though a large scale trial was not performed, we expect the system to scale very well to larger setups. Additionally, the platform is open-source, enabling other users to easily build upon our work and perform application-specific optimisations.


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