M2M
M2M
Machine to machine
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...
Evaluation on the impact of digital transformation on the economic resilience of the energy industry in the context of artificial intelligence
15/12/2022 -
In recent years, the energy industry based on energy resources has achieved rapid development, but under the background of green development strategy, traditional energy companies are also in...
Distributed Ledger Technology for Trust Management Optimisation in M2M
06/06/2019 -
Decentralised environments with a high number of end-users and M2M devices used in several M2M services increase the importance of a secure trust management and comprehensive trust evaluation...
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...
Economic assessment for additive manufacturing of automotive end-use parts through digital light processing (DLP)
07/07/2021 -
Within the last years, digital light processing (DLP) became a viable solution for the manufacturing of end-use parts in various industries among other additive manufacturing (AM) processes. As...
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...
A hybrid machine-learning model for predicting the waste generation rate of building demolition projects
-
Information on waste generation rate (WGR) is useful for waste management. Recently, several studies have been conducted to predict WGR using artificial intelligence (AI) to the end of realizing...
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
-
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
-
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...
Linked Open Government Data to Predict and Explain House Prices: The Case of Scottish Statistics Portal
-
Accurately estimating the prices of houses is important for various stakeholders including house owners, real estate agencies, government agencies, and policy-makers. Towards this end, traditional...