scholarly journals An Approach Based on Fog Computing for Providing Reliability in IoT Data Collection: A Case Study in a Colombian Coffee Smart Farm

2020 ◽  
Vol 10 (24) ◽  
pp. 8904
Author(s):  
Ana Isabel Montoya-Munoz ◽  
Oscar Mauricio Caicedo Rendon
Keyword(s):  
Data Collection ◽  
Mean Squared Error ◽  
Fog Computing ◽  
Reliable Data ◽  
Inaccurate Data ◽  
Squared Error ◽  
Smart Farming ◽  
The Internet Of Things

The reliability in data collection is essential in Smart Farming supported by the Internet of Things (IoT). Several IoT and Fog-based works consider the reliability concept, but they fall short in providing a network’s edge mechanisms for detecting and replacing outliers. Making decisions based on inaccurate data can diminish the quality of crops and, consequently, lose money. This paper proposes an approach for providing reliable data collection, which focuses on outlier detection and treatment in IoT-based Smart Farming. Our proposal includes an architecture based on the continuum IoT-Fog-Cloud, which incorporates a mechanism based on Machine Learning to detect outliers and another based on interpolation for inferring data intended to replace outliers. We located the data cleaning at the Fog to Smart Farming applications functioning in the farm operate with reliable data. We evaluate our approach by carrying out a case study in a network based on the proposed architecture and deployed at a Colombian Coffee Smart Farm. Results show our mechanisms achieve high Accuracy, Precision, and Recall as well as low False Alarm Rate and Root Mean Squared Error when detecting and replacing outliers with inferred data. Considering the obtained results, we conclude that our approach provides reliable data collection in Smart Farming.

Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods

scholarly journals Towards Self-Awareness Privacy Protection for Internet of Things Data Collection

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Kok-Seng Wong ◽  
Myung Ho Kim
Keyword(s):  
Data Collection ◽  
Internet Of Things ◽  
Personal Data ◽  
Self Awareness ◽  
Privacy Concern ◽  
Goods And Services ◽  
Data Collector ◽  
Inaccurate Data ◽  
Secure Protocol ◽  
The Internet Of Things

The Internet of Things (IoT) is now an emerging global Internet-based information architecture used to facilitate the exchange of goods and services. IoT-related applications are aiming to bring technology to people anytime and anywhere, with any device. However, the use of IoT raises a privacy concern because data will be collected automatically from the network devices and objects which are embedded with IoT technologies. In the current applications, data collector is a dominant player who enforces the secure protocol that cannot be verified by the data owners. In view of this, some of the respondents might refuse to contribute their personal data or submit inaccurate data. In this paper, we study a self-awareness data collection protocol to raise the confidence of the respondents when submitting their personal data to the data collector. Our self-awareness protocol requires each respondent to help others in preserving his privacy. The communication (respondents and data collector) and collaboration (among respondents) in our solution will be performed automatically.

scholarly journals PERAN MANAJEMEN SDM DALAM LEMBAGA PENDIDIKAN UNTUK MENINGKATKAN MUTU PENDIDIK

2020 ◽  
Vol 2 (1) ◽  
pp. 33-44
Author(s):  
Ita Nurmalasari ◽  
Dewi Zainul Karimah
Keyword(s):  
Data Collection ◽  
Human Resources ◽  
Islamic Education ◽  
Observation Study ◽  
Study Program ◽  
Education Management ◽  
Data Collection Technique

This study examines the role of human resource management in improving the quality of educators. This research uses a qualitative approach with case study. This research site is in MTs Nu Ma'arif Kemiri, Purworejo Regency. The data collection technique used by researchers is interview observation. In this study, the object of research is the Role of Human Resources to Achieve Workforce Quality in MTs Nu Ma'arif Kemiri. Research data collection using descriptive observation, interview or qualitative methods. This interview observation study was conducted by lecturers and students of Islamic Education Management Study Program with student WK in MTs Nu Ma'arifKemiri. This activity aims to observe the Quality of Human Resources Workers conducted by MTs Nu Ma'arif Kemiri.

scholarly journals PERAN KEPEMIMPINAN KIAI DALAM MENINGKATKAN MUTU PENDIDIKAN (STUDI KASUS DI PONDOK PESANTREN BAHRUL MAGHFIROH KOTA MALANG)

2019 ◽  
Vol 1 (1) ◽  
pp. 18
Author(s):  
Syafi'i Syafi'i
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Qualitative Methods ◽  
Human Resource ◽  
Qualitative Method ◽  
Boarding School ◽  
Quality Of Education

The leadership of the kiai becomes very important in Islamic boarding school because the development of the quality of pesantren education depends on the competence of the leader, the meaning of the leader here is the kiai or caretaker of the boarding school. This study aims to describe the first role of leadership in improving the quality of education, secondly the leadership of kiai that is effective in improving the quality of education in Islamic boarding schools.This research uses a qualitative method, with a case study in Bahrul Maghfiroh Islamic Boarding School in Malang. Data collection was carried out using interview, observation, and documentation and observation techniques. Data analysis uses descriptive qualitative methods and inductive thinking patterns. The purpose is to analyze the data obtained from field objects, and then to be related to relevant theories.The results showed: 1) The role of the kiai in improving quality in the Bahrul Maghfiroh Islamic boarding school in Malang is as a manager, educator, human resource empowerment, decision maker, attainee of the pesantren, motivator and supervisor. 2) Effective kiai leadership is leadership that builds cooperation with kiai or other institutions, regenerates kiai and builds good relations with the community.

scholarly journals IoT Security Configurability with Security-by-Contract

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4121 ◽  
Author(s):  
Alberto Giaretta ◽  
Nicola Dragoni ◽  
Fabio Massacci
Keyword(s):  
Internet Of Things ◽  
Fog Computing ◽  
Holistic Approach ◽  
The Internet ◽  
Iot Security ◽  
Iot Devices ◽  
Work First ◽  
The Internet Of Things

Cybersecurity is one of the biggest challenges in the Internet of Things (IoT) domain, as well as one of its most embarrassing failures. As a matter of fact, nowadays IoT devices still exhibit various shortcomings. For example, they lack secure default configurations and sufficient security configurability. They also lack rich behavioural descriptions, failing to list provided and required services. To answer this problem, we envision a future where IoT devices carry behavioural contracts and Fog nodes store network policies. One requirement is that contract consistency must be easy to prove. Moreover, contracts must be easy to verify against network policies. In this paper, we propose to combine the security-by-contract (S × C) paradigm with Fog computing to secure IoT devices. Following our previous work, first we formally define the pillars of our proposal. Then, by means of a running case study, we show that we can model communication flows and prevent information leaks. Last, we show that our contribution enables a holistic approach to IoT security, and that it can also prevent unexpected chains of events.

Electricity Consumption Analysis Using Demographic Variables Case Study – Nakhonratchasima, Thailand

2013 ◽  
Vol 734-737 ◽  
pp. 1679-1682
Author(s):  
Sureeporn Meehom ◽  
Nopphadon Khodpun
Keyword(s):  
High Speed ◽  
Mean Squared Error ◽  
Mean Absolute Error ◽  
Electricity Consumption ◽  
Absolute Error ◽  
Demographic Variables ◽  
Resources Management ◽  
Squared Error ◽  
High Speed Diesel

Electricity energy is vital in social and economic for nation development. The electricity consumption analysis plays an important role for sustainable energy and electricity resources management in the future. In this paper, the influence of demographical variables on the annual electricity consumption in Nakhonratchasima has been investigated by multiple regression analysis. It is founded that the electricity consumption correlated with four demographic variables, which are the number of electricity consumers, the amount of high speed diesel usages, the number of industrial factory and the number of employed labor force. The historical electricity consumption and all variables for the period 20022010 have been analyzed in 8 models for electricity prediction in 2011. In conclusion, the effective model has been selected by comparison of adjusted R2, mean absolute error (MAE) and root mean squared error (RMSE) of the proposed models. Model 8 is acceptable in relation to electricity consumption analysis with adjusted-R2, RMSE and MAE equal to 0.9980, 0.7540% and 0.6095% respectively. The results indicate that the model using all four variables has strong ability to predict future annual electricity consumption with 4,195,837,877 kWh in 2011.

scholarly journals Triadic IBD coefficients and applications to estimating pairwise relatedness

2007 ◽  
Vol 89 (3) ◽  
pp. 135-153 ◽  
Author(s):  
JINLIANG WANG
Keyword(s):  
Genetic Relatedness ◽  
Mean Squared Error ◽  
Likelihood Method ◽  
Research Areas ◽  
Squared Error ◽  
Identical By Descent ◽  
Moment Estimators ◽  
Overall Performance ◽  
Methodological Studies

SummaryKnowledge of the genetic relatedness among individuals is essential in diverse research areas such as behavioural ecology, conservation biology, quantitative genetics and forensics. How to estimate relatedness accurately from genetic marker information has been explored recently by many methodological studies. In this investigation I propose a new likelihood method that uses the genotypes of a triad of individuals in estimating pairwise relatedness (r). The idea is to use a third individual as a control (reference) in estimating the r between two other individuals, thus reducing the chance of genes identical in state being mistakenly inferred as identical by descent. The new method allows for inbreeding and accounts for genotype errors in data. Analyses of both simulated and human microsatellite and SNP datasets show that the quality of r estimates (measured by the root mean squared error, RMSE) is generally improved substantially by the new triadic likelihood method (TL) over the dyadic likelihood method and five moment estimators. Simulations also show that genotyping errors/mutations, when ignored, result in underestimates of r for related dyads, and that incorporating a model of typing errors in the TL method improves r estimates for highly related dyads but impairs those for loosely related or unrelated dyads. The effects of inbreeding were also investigated through simulations. It is concluded that, because most dyads in a natural population are unrelated or only loosely related, the overall performance of the new triadic likelihood method is the best, offering r estimates with a RMSE that is substantially smaller than the five commonly used moment estimators and the dyadic likelihood method.

Developing an effective renovation plan: the influence of data collection tools

2018 ◽  
Vol 36 (1) ◽  
pp. 63-76 ◽  
Author(s):  
Edoghogho Ogbeifun ◽  
Charles Mbohwa ◽  
Jan-Harm Christiaan Pretorius
Keyword(s):  
Qualitative Research ◽  
Data Collection ◽  
Single Case ◽  
Education Institution ◽  
Condition Index ◽  
Facilities Management ◽  
Content Type ◽  
History Of

Purpose All built facility begins to show signs of deterioration immediately after the facility is completed and put to use, thus necessitating routine maintenance. Increase in defects due to age, usage, and other factors, requires extensive maintenance activities known as renovation. The data used for a typical renovation plan can be collected using the condition assessment (CA) tool which depends on physical inspection of the defects or through a facility condition index which hinges on harnessing and analyzing the information in the operational history of the facility. The purpose of this paper is to examine the quality of a typical renovation plan using both tools. Design/methodology/approach The single case study of qualitative research was adopted. The data were collected through the principle of semi-structured questionnaire complemented with interviews and document analysis. The documents include periodic operational reports and a CA report used for planned renovation exercise of the Facilities Management (FM) Unit in a higher education institution in South Africa. Findings The findings revealed that although the FM Unit produces periodic reports, but there was no evidence of detailed analysis of the reports. Therefore, the programmed renovation exercises are based purely on the information from a CA. Research limitations/implications This research is a single site case study of qualitative research; the data collected are limited and not sufficient for generalization of the results. Furthermore, the lack of record of the analysis of the operational history in the periodic reports negatively affected the computation of facilities condition index (FCI). Thus it was not possible to demonstrate the strength of FCI over CA from empirical information. Originality/value The quality of a typical renovation plan is influenced by the tool used for data collection. Although the CA tool is commonly used, experience shows that the renovation exercise developed from such records is prone to many execution setbacks, such as frequent scope changes and the associated cost and time overruns. These setbacks can be minimized if the FCI is used as the tool for data collection.

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