Internet of things (IoT) applications in orthopaedics.
Ontology highlight
ABSTRACT:
SUBMITTER: Haleem A
PROVIDER: S-EPMC6977530 | biostudies-literature | 2020 Feb
REPOSITORIES: biostudies-literature
Publications
Internet of things (IoT) applications in orthopaedics.
Haleem Abid A Javaid Mohd M Khan Ibrahim Haleem IH
Journal of clinical orthopaedics and trauma 20190712 Suppl 1
Similar Datasets
Project description:The Internet of Things (IoT) provides a simple framework to control online devices easily. IoT is now a commonplace tool used by technology companies but is rarely used in biology experiments. IoT can benefit cloud biology research through alarm notifications, automation, and the real-time monitoring of experiments. We developed an IoT architecture to control biological devices and implemented it in lab experiments. Lab devices for electrophysiology, microscopy, and microfluidics were created from the ground up to be part of a unified IoT architecture. The system allows each device to be monitored and controlled from an online web tool. We present our IoT architecture so other labs can replicate it for their own experiments.
| S-EPMC10305744 | biostudies-literature
Project description:Internet of things (IoT) applications in smart agricultural systems vary from monitoring climate conditions, automating irrigation systems, greenhouse automation, crop monitoring and management, and crop prediction, up to end-to-end autonomous farm management systems. One of the main challenges to the advancement of IoT systems for the agricultural domain is the lack of training data under operational environmental conditions. Most of the current designs are based on simulations and artificially generated data. Therefore, the essential first step is studying and understanding the finely tuned and highly sensitive mechanism plants have developed to sense, respond, and adapt to changes in their environment, and their behavior under field and controlled systems. Therefore, this study was designed to achieve two specific objectives; to develop low-cost IoT components from basic building blocks, and to study the performance of the developed systems, and generate real-time experimental data, with and without plants. Low-cost IoT devices developed locally were used to convert existing basic polytunnels to semi-controlled and monitoring-only polytunnels. Their performances were analyzed and compared with each other based on several matrices while maintaining the planted tomato variety and agronomic practices similar. The developed system performed as expected suggesting the possibility of commercial applications and research purposes.
| S-EPMC10212138 | biostudies-literature
Project description:In the traditional irrigation process, a huge amount of water consumption is required which leads to water wastage. To reduce the wasting of water for this tedious task, an intelligent irrigation system is urgently needed. The era of machine learning (ML) and the Internet of Things (IoT) brings it is a great advantage of building an intelligent system that performs this task automatically with minimal human effort. In this study, an IoT enabled ML-trained recommendation system is proposed for efficient water usage with the nominal intervention of farmers. IoT devices are deployed in the crop field to precisely collect the ground and environmental details. The gathered data are forwarded and stored in a cloud-based server, which applies ML approaches to analyze data and suggest irrigation to the farmer. To make the system robust and adaptive, an inbuilt feedback mechanism is added to this recommendation system. The experimentation, reveals that the proposed system performs quite well on our own collected dataset and National Institute of Technology (NIT) Raipur crop dataset.
| S-EPMC8237332 | biostudies-literature
Project description:With the increasing demand for the use of technology in all matters of daily life and business, the demand has increased dramatically to transform business electronically especially regards COVID-19. The Internet of Things (IoT) has greatly helped in accomplishing tasks. For example, at a high temperature, it would be possible to switch on the air conditioner using a personal mobile device while the person is in the car. The Internet of Things (IoT) eases lots of tasks. A wireless sensor network is an example of IoT. Wireless sensor network (WSN) is an infrastructure less self-configured that can monitor environmental conditions such as vibration, temperature, wind speed, sound, pressure, and vital signs. Thus, WSNs can occur in many fields. Smart homes give a good example of that. The security concern is important, and it is an essential requirement to ensure secure data. Different attacks and privacy concerns can affect the data. Authentication is the first defence line against threats and attacks. This study proposed a new protocol based on using four factors of authentication to improve the security level in WSN to secure communications. The simulation results prove the strength of the proposed method which reflects the importance of the usage of such protocol in authentication areas.
| S-EPMC11232626 | biostudies-literature
Project description:Modern internet of things (IoTs) and ubiquitous sensor networks could potentially take advantage of chemically sensitive nanomaterials and nanostructures. However, their heterogeneous integration with other electronic modules on a networked sensor node, such as silicon-based modulators and memories, is inherently challenging because of compatibility and integration issues. Here we report a novel paradigm for sensing modulators: a graphene field-effect transistor device that directly modulates a radio frequency (RF) electrical carrier signal when exposed to chemical agents, with a memory effect in its electrochemical history. We demonstrated the concept and implementation of this graphene-based sensing modulator through a frequency-modulation (FM) experiment conducted in a modulation cycle consisting of alternating phases of air exposure and ethanol or water treatment. In addition, we observed an analog memory effect in terms of the charge neutrality point of the graphene, V cnp, which strongly influences the FM results, and developed a calibration method using electrochemical gate-voltage pulse sequences. This graphene-based multifunctional device shows great potential for use in a simple, low-cost, and ultracompact nanomaterial-based nodal architecture to enable continuous, real-time event-based monitoring in pervasive healthcare IoTs, ubiquitous security systems, and other chemical/molecular/gas monitoring applications.
| S-EPMC6444719 | biostudies-literature
Project description:Quick Response (QR) codes are a gateway to the Internet of things (IoT) due to the growing use of smartphones/mobile devices and its properties like fast and easy reading, capacity to store more information than that found in conventional codes, and versatility associated to the rapid and simplified access to information. Challenges encompass the enhancement of storage capacity limits and the evolution to a smart label for mobile devices decryption applications. Organic-inorganic hybrids with europium (Eu3+) and terbium (Tb3+) ions are processed as luminescent QR codes that are able to simultaneously double the storage capacity and sense temperature in real time using a photo taken with the charge-coupled device of a smartphone. The methodology based on the intensity of the red and green pixels of the photo yields a maximum relative sensitivity and minimum temperature uncertainty of the QR code sensor (293 K) of 5.14%?·?K-1 and 0.194 K, respectively. As an added benefit, the intriguing performance results from energy transfer involving the thermal coupling between the Tb3+-excited level (5D4) and the low-lying triplet states of organic ligands, being the first example of an intramolecular primary thermometer. A mobile app is developed to materialize the concept of temperature reading through luminescent QR codes.
| S-EPMC6774024 | biostudies-literature
Project description: Not available
| S-EPMC8411163 | biostudies-literature
Project description:Supply Chain Management (SCM) is one of the key aspects of making agriculture sector more competitive in India. India and other developing countries arefacing issues for coordination of their Agriculture Food Supply Chain Management (AFSCM) as not having technical and resources support; especially in natural disaster condition like recent COVID-19 outbreak. The purpose of this research is to develop anInternet of Things (IoT) based efficient and supportive coordinating system for enhancing the coordinating mechanism in AFSC under natural outbreaks. With the help of a literature review and experts’ inputs, seven enablers have been identified by grouping thirty sub enablers. Further, ISM methodology has been employed for developing a framework for enablers’ relationships to improve the coordination in the AFSC for taking strategic and operational decisions. After that, DEMATELtechnique is utilised to develop the causal and effectrelationships between all the identified enablers of a coordination system in IoT based AFSC. It has been noticed that‘Top Management Support (TMS)’ is the main driver by MICMAC analysis and categorised in a cause group based on (R-C) value. Further, the coordination index of the entire model is calculated based on the Cleveland theory. This paper also discussed a case study of the sugar mill industry. This paper also discussed stakeholder theory in developing IoT based coordination system of AFSC. Further, theoretical contribution may also guide the managers of the organisation in developing their strategies by using Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis based on Cleveland index.
| S-EPMC7500993 | biostudies-literature
Project description:The Internet of Underwater Things (IoUT) is a novel class of Internet of Things (IoT), and is defined as the network of smart interconnected underwater objects. IoUT is expected to enable various practical applications, such as environmental monitoring, underwater exploration, and disaster prevention. With these applications, IoUT is regarded as one of the potential technologies toward developing smart cities. To support the concept of IoUT, Underwater Wireless Sensor Networks (UWSNs) have emerged as a promising network system. UWSNs are different from the traditional Territorial Wireless Sensor Networks (TWSNs), and have several unique properties, such as long propagation delay, narrow bandwidth, and low reliability. These unique properties would be great challenges for IoUT. In this paper, we provide a comprehensive study of IoUT, and the main contributions of this paper are threefold: (1) we introduce and classify the practical underwater applications that can highlight the importance of IoUT; (2) we point out the differences between UWSNs and traditional TWSNs, and these differences are the main challenges for IoUT; and (3) we investigate and evaluate the channel models, which are the technical core for designing reliable communication protocols on IoUT.
| S-EPMC5539468 | biostudies-other
Project description:Brain-computer interfaces (BCIs) have enabled individuals to control devices such as spellers, robotic arms, drones, and wheelchairs, but often these BCI applications are restricted to research laboratories. With the advent of virtual reality (VR) systems and the internet of things (IoT) we can couple these technologies to offer real-time control of a user's virtual and physical environment. Likewise, BCI applications are often single-use with user's having no control outside of the restrictions placed upon the applications at the time of creation. Therefore, there is a need to create a tool that allows users the flexibility to create and modularize aspects of BCI applications for control of IoT devices and VR environments. Using a popular video game engine, Unity, and coupling it with BCI2000, we can create diverse applications that give the end-user additional autonomy during the task at hand. We demonstrate the validity of controlling a Unity-based VR environment and several commercial IoT devices via direct neural interfacing processed through BCI2000.
| S-EPMC6157750 | biostudies-literature