scholarly journals Uplink and Downlink Variation in Drone Technology for Cloud, Edge, Fog and Smart Dust Integrated IoT Architecture: Demonstrated Over WSNs

2021 ◽  
Vol 2089 (1) ◽  
pp. 012023
Author(s):  
Jayantkumar Dorave ◽  
Ritesh Sadiwala
Keyword(s):  
Network Architecture ◽  
New Technology ◽  
Cost Effective ◽  
Raspberry Pi ◽  
Processing Capacity ◽  
Time Analysis ◽  
Substantial Impact ◽  
Smart Dust ◽  
Iot Devices ◽  
The One

Abstract IoT concepts are heavily applicable in drone communication integrated with different network architecture for optimization. Distributing the burden allows more IoT devices to execute calculations, rather than everything being done on the cloud. There are numerous IoT designs that have emerged as a result of this. By relocating calculations away from the cloud, these designs make use of the enhanced processing capacity of the devices. Based on our needs, we’ve limited it down to four architectures, each of which we have discussed for optimized flow useful in drone technology. We have also applied the one live dataset for the test drone using raspberry pi processor system powered with for end-to-end drone communication establishment. The analysis of downlink and uplink were studied for time analysis for IoT architecture using drone cell characteristics. New technology makes it possible to implement drone cell (DC) connectivity, which is highly flexible and cost-effective for the gathering of Internet-of-things (IoT) data when terrestrial networks are not yet accessible. DC’s flight path has a substantial impact on data collecting systems.

scholarly journals IoT Botnet Detection Using Various One-Class Classifiers

2020 ◽  
pp. 1-20
Author(s):  
Mehedi Hasan Raj ◽  
A. N. M. Asifur Rahman ◽  
Umma Habiba Akter ◽  
Khayrun Nahar Riya ◽  
Anika Tasneem Nijhum ◽  
...  
Keyword(s):  
Network Flow ◽  
Cost Effective ◽  
Support Vector ◽  
Good Precision ◽  
Accuracy Score ◽  
Botnet Detection ◽  
The People ◽  
Iot Devices ◽  
Set Up ◽  
The One

Nowadays, the Internet of Things (IoT) is a common word for the people because of its increasing number of users. Statistical results show that the users of IoT devices are dramatically increasing, and in the future, it will be to an ever-increasing extent. Because of the increasing number of users, security experts are now concerned about its security. In this research, we would like to improve the security system of IoT devices, particularly in IoT botnet, by applying various machine learning (ML) techniques. In this paper, we have set up an approach to detect botnet of IoT devices using three one-class classifier ML algorithms. The algorithms are: one-class support vector machine (OCSVM), elliptic envelope (EE), and local outlier factor (LOF). Our method is a network flow-based botnet detection technique, and we use the input packet, protocol, source port, destination port, and time as features of our algorithms. After a number of preprocessing steps, we feed the preprocessed data to our algorithms that can achieve a good precision score that is approximately 77–99%. The one-class SVM achieves the best accuracy score, approximately 99% in every dataset, and EE’s accuracy score varies from 91% to 98%; however, the LOF factor achieves lowest accuracy score that is from 77% to 99%. Our algorithms are cost-effective and provide good accuracy in short execution time.

Teletinnitus Program at the VA Gulf Coast Veterans Health Care System

2014 ◽  
Vol 4 (1) ◽  
pp. 23-29
Author(s):  
Constance Hilory Tomberlin
Keyword(s):  
Health Care ◽  
Patient Satisfaction ◽  
Patient Care ◽  
Health Care System ◽  
Gulf Coast ◽  
New Technology ◽  
Cost Effective ◽  
Veterans Health ◽  
Potential Benefits ◽  
Care System

There are a multitude of reasons that a teletinnitus program can be beneficial, not only to the patients, but also within the hospital and audiology department. The ability to use technology for the purpose of tinnitus management allows for improved appointment access for all patients, especially those who live at a distance, has been shown to be more cost effective when the patients travel is otherwise monetarily compensated, and allows for multiple patient's to be seen in the same time slots, allowing for greater access to the clinic for the patients wishing to be seen in-house. There is also the patient's excitement in being part of a new technology-based program. The Gulf Coast Veterans Health Care System (GCVHCS) saw the potential benefits of incorporating a teletinnitus program and began implementation in 2013. There were a few hurdles to work through during the beginning organizational process and the initial execution of the program. Since the establishment of the Teletinnitus program, the GCVHCS has seen an enhancement in patient care, reduction in travel compensation, improvement in clinic utilization, clinic availability, the genuine excitement of the use of a new healthcare media amongst staff and patients, and overall patient satisfaction.

scholarly journals Sprouting of Sorghum (Sorghum bicolor [L.] Moench): Effect of Drying Treatment on Protein and Starch Features

Foods ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 407 ◽  
Author(s):  
Mia Marchini ◽  
Alessandra Marti ◽  
Claudia Folli ◽  
Barbara Prandi ◽  
Tommaso Ganino ◽  
...  
Keyword(s):  
Food Production ◽  
Cost Effective ◽  
High Exposure ◽  
Effective Technology ◽  
Drying Treatment ◽  
Higher Temperature ◽  
Lower Temperature ◽  
The One ◽  
Drying Conditions ◽  
Sorghum Bicolor L

The nutritional and physicochemical properties of sorghum proteins and starch make the use of this cereal for food production challenging. Sprouting is a cost-effective technology to improve the nutritional and functional profile of grains. Two drying treatments were used after sorghum sprouting to investigate whether the drying phase could improve the protein and starch functionalities. Results showed that the drying treatment at lower temperature/longer time (40 °C for 12 h) extended the enzymatic activity that started during sprouting compared to the one performed at higher temperature/shorter time (50 °C for 6 h). An increased protein hydrolysis and water- and oil-holding capacity were found in the flour obtained by the former treatment. Higher protein matrix hydrolysis caused high exposure of starch to enzymes, thus increasing its digestibility, while worsening the technological functionality. Overall, modulating drying conditions could represent a further way, in addition to sprouting, to improve sorghum flour’s nutritional profile.

scholarly journals Practical Cross-Layer Radio Frequency-Based Authentication Scheme for Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4034
Author(s):  
Arie Haenel ◽  
Yoram Haddad ◽  
Maryline Laurent ◽  
Zonghua Zhang
Keyword(s):  
Internet Of Things ◽  
Radio Frequency ◽  
Real Life ◽  
Computation Time ◽  
Cost Effective ◽  
Battery Life ◽  
Cross Layer ◽  
Security Level ◽  
Cost Of Energy ◽  
Iot Devices

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.

scholarly journals Exoskeletons for all: The interplay between exoskeletons, inclusion, gender, and intersectionality

2020 ◽  
Vol 11 (1) ◽  
pp. 217-227 ◽  
Author(s):  
Roger Andre Søraa ◽  
Eduard Fosch-Villaronga
Keyword(s):  
New Technology ◽  
Health Condition ◽  
End Users ◽  
Target Market ◽  
Inclusion Criteria ◽  
Wearable Robot ◽  
Exclusion Criteria ◽  
Intersectionality Theory ◽  
Design Choice ◽  
The One

AbstractIn this article, we investigate the relation between gender and exoskeleton development through the lens of intersectionality theory. Exoskeleton users come in a wide variety of shapes, sizes, and genders. However, it is often the case that wearable robot engineers do not develop such devices primarily on the premise that the product should fit as many end users as possible. Instead, designers tend to use the one-size-fits-all approach – a design choice that seems legitimate from the return of an investment viewpoint but that may not do as much justice to end users. Intended users of exoskeletons have a series of user criteria, including height, weight, and health condition, in the case of rehabilitation. By having rigid inclusion criteria for whom the intended user of the technology can be, the exclusion criteria will grow in parallel. The implications and deep-rootedness of gender and diversity considerations in practices and structural systems have been largely disregarded. Mechanical and robot technology were historically seen as part of a distinct male sphere, and the criteria used today to develop new technology may reflect the biases that existed in another time that should no longer be valid. To make this technology available for all, we suggest some tools to designers and manufacturers to help them think beyond their target market and be more inclusive.

scholarly journals Gas Detection and Identification Using Multimodal Artificial Intelligence Based Sensor Fusion

2021 ◽  
Vol 4 (1) ◽  
pp. 3
Author(s):  
Parag Narkhede ◽  
Rahee Walambe ◽  
Shruti Mandaokar ◽  
Pulkit Chandel ◽  
Ketan Kotecha ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Network Architecture ◽  
Cost Effective ◽  
Sensor Data ◽  
Dense Layer ◽  
Gaseous Emissions ◽  
Multiple Sensors ◽  
Single Output ◽  
Novel Approach ◽  
Single Sensor

With the rapid industrialization and technological advancements, innovative engineering technologies which are cost effective, faster and easier to implement are essential. One such area of concern is the rising number of accidents happening due to gas leaks at coal mines, chemical industries, home appliances etc. In this paper we propose a novel approach to detect and identify the gaseous emissions using the multimodal AI fusion techniques. Most of the gases and their fumes are colorless, odorless, and tasteless, thereby challenging our normal human senses. Sensing based on a single sensor may not be accurate, and sensor fusion is essential for robust and reliable detection in several real-world applications. We manually collected 6400 gas samples (1600 samples per class for four classes) using two specific sensors: the 7-semiconductor gas sensors array, and a thermal camera. The early fusion method of multimodal AI, is applied The network architecture consists of a feature extraction module for individual modality, which is then fused using a merged layer followed by a dense layer, which provides a single output for identifying the gas. We obtained the testing accuracy of 96% (for fused model) as opposed to individual model accuracies of 82% (based on Gas Sensor data using LSTM) and 93% (based on thermal images data using CNN model). Results demonstrate that the fusion of multiple sensors and modalities outperforms the outcome of a single sensor.

scholarly journals Genotyping of GATA4 Gene Variant (G296S) in Malaysian Congenital Heart Disease Subjects by Real-Time PCR High Resolution Melting Analysis

2013 ◽  
Vol 32 (2) ◽  
pp. 152-157
Author(s):  
Nora Fawzi ◽  
Ramachandran Vasudevan ◽  
Patimah Ismail ◽  
Mazeni Alwi ◽  
Ahmad Fazli Abdul Aziz ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
High Resolution ◽  
Congenital Heart ◽  
High Resolution Melting ◽  
New Technology ◽  
Cost Effective ◽  
Study Cohort ◽  
Hrm Analysis ◽  
Melting Analysis

Summary Background: Congenital heart disease (CHD) is the most common birth defect; however, the underlying etiology is unrecognized in the majority of cases. GATA-binding protein 4 (GATA4), a cardiac transcription factor gene, has a crucial role in the cardiogenesis process; hence, a number of heterozygote sequence variations were identified as a cause of CHD. G296S heterozygote variant is the most frequently reported GATA4 gene sequence alteration. This study aims to investigate the role of G296S variant of the GATA4 gene in Malaysian CHD subjects. Methods: We have investigated 86 Malaysian CHD subjects with cardiac septation defects for the presence of the GATA4 gene heterozygote variant (G296S) by the new technology of high resolution melting (HRM) analysis. Results: Genotyping of G296S (c.886G>A) by HRM analysis shows that all the sample genotypes were of the wild GG type genotype and the heterozygote mutant GA genotype was totally absent from this study cohort. Conclusions: The results of our study showed that the G296S variant of the GATA4 gene was not associated with the development of CHD in Malaysian subjects. The use of HRM analysis proved a cost-effective, high-throughput, specific and sensitive genotyping technique which eliminates the need for unnecessary sequencing.

IoT Based Bus Tracking System

2021 ◽  
Vol 9 (VI) ◽  
pp. 2889-2893
Author(s):  
Miss Payal W. Paratpure
Keyword(s):  
Tracking System ◽  
Cost Effective ◽  
Raspberry Pi ◽  
Accurate Estimation ◽  
Time Of Arrival ◽  
Test Results ◽  
Cloud Server ◽  
Bus Operator ◽  
Gps Device

Tracking of public bus location requires a GPS device to be installed, and lots of bus operators in developing countries don't have such an answer in situ to supply an accurate estimation of bus time of arrival (ETA). Without ETA information, it's very difficult for the overall public to plan their journey effectively. In this paper, implementation of an innovative IOT solution to trace the real time location of buses without requiring the deployment of a GPS device is discussed. It uses Bluetooth Low Energy (BLE) proximity beacon to trace the journey of a bus by deploying an Estimate location beacon on the bus. BLE detection devices (Raspberry Pi 4) are installed at selected bus stops along the path to detect the arrival of buses. Once detected, the situation of the bus is submitted to a cloud server to compute the bus ETAs. A field trial is currently being conducted in Johor, Malaysia together with an area bus operator on one single path. Our test results showed that the detection of BLE beacons is extremely accurate and it's feasible to trace the situation of buses without employing a GPS device during a cost-effective way.

scholarly journals Variations in Moisture Supply from the Mediterranean Sea during Meteorological Drought Episodes over Central Europe

Atmosphere ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 278 ◽  
Author(s):  
Milica Stojanovic ◽  
Anita Drumond ◽  
Raquel Nieto ◽  
Luis Gimeno
Keyword(s):  
Linear Relationship ◽  
Mediterranean Sea ◽  
Central Europe ◽  
Linear Regression Analysis ◽  
Meteorological Drought ◽  
Time Analysis ◽  
Moisture Supply ◽  
The Mediterranean ◽  
The One ◽  
Annual Summer

The climate in Central Europe (CEU) during the 20th century is characterized by an overall temperature increase. Severe and prolonged drought events began occurring towards the end and these have continued into the 21st century. This study aims to analyze variations in the moisture supply from the Mediterranean Sea (MDS) during meteorological drought episodes occurring over the CEU region over the last three decades. A total of 51 meteorological drought episodes (22 with summer onsets, and 29 with winter) are identified over the CEU during the period 1980–2015 through the one-month Standardized Precipitation Evapotranspiration Index (SPEI-1), and their respective indicators, including duration, severity, intensity, and peak values, are then computed. Lagrangian forward-in-time analysis reveals that negative anomalies of moisture coming from the MDS prevail in all episodes except seven. Linear regression analysis between variations in the MDS anomalies and indicators of the drought episodes shows a significant linear relationship between severity, duration, peak values (winter), and MDS anomalies, which implies that drought episodes last longer and are more severe with an increase in the negative anomaly of moisture supply from the MDS. Nevertheless, no linear relationship is found between the intensity and peak values (annual, summer) of drought episodes and anomalies in the moisture contribution from the MDS.

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