Internet de las Cosas
Internet de las Cosas
Data on Field Canals Improvement Projects for Cost Prediction Using Artificial Intelligence
19/05/2020 -
Field Canals Improvement Projects is an important sustainable project to save fresh water in our world. Machine learning and artificial intelligence (AI) needs sufficient dataset size to model and...
Applied artificial intelligence for predicting construction projects delay
25/09/2021 -
This study presents evidence of a developed ensemble of ensembles predictive model for delay prediction – a global phenomenon that has continued to strangle the construction sector despite...
Performance Evaluation of an M2M Platform in Different Deployment Setups
19/05/2016 -
Machine-to-Machine (M2M) communication technology is emerging as one of the major trends shaping the development of services in Smart Cities. However, there are grand challenges related to...
The nature of the Artificially Intelligent Firm - An economic investigation into changes that AI brings to the firm
28/03/2020 -
With the arrival of Artificial Intelligence (AI), the nature of the firm is changing and economic theory can provide guidance to businesses as well as to politics when formulating adequate...
Implementing challenges of artificial intelligence: Evidence from public manufacturing sector of an emerging economy
01/10/2021 -
The growing Artificial Intelligence (AI) age has been flooded with several innovations in algorithmic machine learning that may bring significant impacts to industries such as healthcare,...
An effective approach for software project effort and duration estimation with machine learning algorithms
28/11/2017 -
During the last two decades, there has been substantial research performed in the field of software estimation using machine learning algorithms that aimed to tackle deficiencies of traditional...
On-demand monitoring of construction projects through a game-like hybrid application of BIM and machine learning
27/11/2019 -
While unavoidable, inspections, progress monitoring, and comparing as-planned with as-built conditions in construction projects do not readily add tangible intrinsic value to the end-users. In...
Predicting long-time contributors for GitHub projects using machine learning
10/05/2021 -
Many organizations develop software systems using open source software (OSS), which is risky due to the high possibility of losing support. Contributors are critical for the survival of OSS...
The impact of entrepreneurship orientation on project performance: A machine learning approach
15/01/2020 -
Recent studies in project management have shown the important role of entrepreneurship orientation of the individuals in project performance. Although identifying the role of entrepreneurship...
Optimized machine learning modelling for predicting the construction cost and duration of tunnelling projects
11/05/2022 -
Predicting duration and cost of tunnelling projects is an essential factor in determining the usefulness of a decision-making system. Therefore, research on the duration and cost of tunnels'...
Prediction of Risk Percentage in Software Projects by Training Machine Learning Classifiers
07/08/2021 -
Recently, software project failures have been increasing due to lack of planning and budget constraints. In this regard, identifying the suitable software model with the consideration of risk...
Machine learning-based cost predictive model for better operating expenditure estimations of U.S. light rail transit projects
11/04/2022 -
Inaccurate forecasts of operating expenditures (OPEX) during the planning phase for new Light Rail Transit (LRT) projects in the United States underestimated future costs by up to 45% (Harmatuck,...
Machine learning based success prediction for crowdsourcing software projects
20/04/2021 -
Competitive Crowdsourcing Software Development is an online software development paradigm, promises the innovative, cost effective and high quality solutions on time. However, the paradigm is...
Harnessing the power of machine learning analytics to understand food systems dynamics across development projects
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Advances in machine learning and Big Data research offer great potential for international development agencies to leverage the vast information generated from accountability mechanisms to gain...
Estimation of Risk Contingency Budget in Projects using Machine Learning
26/10/2022 -
To manage risks against unexpected cost overruns, project teams use Contingency Budget (CB). Its accurate estimation has been a subject of multiple studies proposing either deterministic or...
A Facial Expression Recognition Approach for Social IoT Frameworks
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Social IoT has become a sensitive topic in the last years, mainly due to the attraction of social networks and the related digital activities amongst the population. These techniques are gaining even...
Automatic Prediction of T2/T3 Staging of Rectal Cancer Based on Radiomics and Machine Learning
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The staging of rectal cancer is very important to determine the treatment plans. This study investigated the relationship between the imaging features and the rectal cancer staging, so that the...
Satellite IoT Based Road Extraction from VHR Images Through Superpixel-CNN Architecture
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In the past few decades, technology has progressively become ineluctable in human lives, primarily due to the growth of certain fields like space technology, Big Data, the Internet of Things (IoT),...
Feature Ranking Importance from Multimodal Radiomic Texture Features using Machine Learning Paradigm: A Biomarker to Predict the Lung Cancer
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The machine learning based techniques for detection of lungs cancer can assist the clinicians in assessing the risk of pulmonary nodules being malignant. We are developing non-invasive methods to...
Crack free metal printing using physics informed machine learning
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Process parameters and thermophysical and mechanical properties of alloys affect cracking which remains a major challenge in metal printing. Cracks occur because of multiple mechanisms and currently,...
Classification of surface settlement levels induced by TBM driving in urban areas using random forest with data-driven feature selection
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Prediction of surface settlements induced by urban area tunneling is challenging owing to the unique tunneling conditions of tunnel sites. This study presents a machine learning (ML) framework to...