Key Features:

IoT-based Telemetric System

Proprietary data acquisition & visualization system works seamlessly with/without existing SCADA system...Read more →

Intelligent Virtual Network

Transform physical water system into Intelligent Virtual Network leveraging AI/deep technology and engineering science of WWI... Read more →

Real-time Predictive Analytics

Predictive Analytics-based tools learn from data and predict future events in real-time based on predefined criteria... Read more →

Smart Prognostic & Diagnostic Alerts

Scrutinize network components, pin-point compromised one and predict vulnerable components ... Read more →

Training HQP & Tech Transfer

Technologies come with high quality trainings on related AI and multiple aspects water network engineering... Read more →

Customer Focused Solutions

Provides network specific customer focused solutions and cherish relationship based business model...Read more →


IoT-based Telemetric System










IoT based data acquisition, processing and visualization technology can provide hydraulic (pressure and flow) and water quality (Temp, pH, Turbidity, Conductivity, water age, etc.) information in real-time

Sensor level deep learning algorithm predicts potential compromised events before the actual occurrences








Intelligent Virtual Network








Inframan's virtualization tool transform every components of the digital water network into smart network components with the power of Artificial Intelligence / deep technology, hydraulic and water quality behavior in the physical water network









Real-time Predictive Analytics








INFRAMAN’s predictive analytics tools learn ingesting online and offline data using proprietary data analytics algorithm and can predict system demand, hydraulic and water quality parameters (e.g., Flow, Pressure, Minimum Night Flow, Savings from Pressure Management, Key Performance Indicators, Economic Level of Leakage, pH, Temperature, Turbidity, Residual Chlorine)








Smart Prognostic & Diagnostic Alerts








INFRAMAN scrutinize every element of network in real-time considering sensor data, digital model, historical data, customer complaints, and social media analytics and can identify hydraulic and water quality failure using proprietary machine learning and soft computing algorithms









Training HQP & Tech Transfer









INFRAMAN provide comprehensive training on our solutions. In addition, INFRAMAN provides hands-on training on various topics hydraulic modeling, water quality modeling and water loss & efficiency management

Key Features:

  • Tailored training based on your current needs and requirements
  • Professional and/ or Expert level contents or topic specifics
  • Conducted by Professional Engineers (P. Eng.) and MIT alumni
  • Comprehensive training materials
  • Hand on practices









Customer Focused Solutions









INFRAMAN clearly understand that every utility has unique challenges. Therefore, our solutions are network specific, however, leverage the proprietary algorithms and engineering solutions for the benifits of every project. We cherish relationship based business model and stand behind for our customers for 24/7.







Applications:

Artificail Intellegence and WWI engineering driven solutions can help multiple aspects of Water Supply Challanages including water efficiency management, hydraulic modeling, water quality modeling, real-time data alert system and Performance Function Evaluation

Water Efficiency

AI inspired propreitary algorithm help to manage leakages. To know our leakage solution... Read more →

Hydraulic Modeling

We provide services for model development from scratch to any stage. To know our modeling solutions... For more →

Asset Management

Deep learning based algorithm can answers the key questions of Asset Management. To know AM solution...... For more →

Water Quality

Whether Chlorine or Chloramine is your disinfectant, we can help. To know our Water Quality solution.... Read more →

Real-time Alerts

Proprietary data visualization system can alert you any abnormality in the system...Read more →

Crisis Management

AI inspired solutions help managing emergency situations.To know our Crisis Management solution... For more →

Water Quality

Whether Chlorine or Chloramine is your secondary disinfectant, INFRAMAN can help you to evaluate system-wise water quality performance.


Sensing and Alerting Water Quality in real-time

INFRAMAN has developed cloud based / local solutions for sensing and visualizing your data in real-time.

Read more →

Water Quality Modeling in Distribution System

INFRAMAN has integrated AI and Gauss-Marquardt-Levenberg Algorithm (GMLA) for model calibration and performance evaluation which provides guaranteed better performance than other algorithms.

Read more →

Performance Function of WTP

INFRAMAN has developed an innovative tool which have following functions: Evaluate performance functions (PFs) of WT units in real time Assess quantitative microbial risk Perform basic statistical analysis Provide graphical results in a dashboard Manual and automatic calculation options

Read more →












Water Efficiency Management







Water Efficiency solutions covers water auditing, pressure management, night flow analysis and modeling of economic level of leakage. Key components of our Water Loss and Efficiency Management (LEM) program are:
  • IWA/AWWA Water Audit
  • Night Flow Analysis
  • Economic Level of Leakage
  • Repair and Field Support.
  • Pressure Management
  • Key Performance Indicators
  • System Design & Evaluation

List of Publications

Journal (In Preparation)

[17] Islam, M.S., Whittle, A. J., Karney, B. W. (2017), Resilience of Water Distribution System under Uncertainties, Will be submitted to the Urban Water Journal

[16] Islam, M.S., Whittle, A. J., (2017), Big Data Analytics in Water Supply System Management: A Generic Application Framework, Will be submitted to the ASCE journal of Computing in Civil Engineering.

[15] Islam, M.S., Whittle, A. J., (2017), Chloramines in a Large Water Distribution System, Will be submitted to the journal of Water Research.


Journal (Published/ Accepted)


[14] Islam, M. S., Sadiq, R., Rodriguez, M. J., Najjaran, H., & Hoorfar, M. (2016). Integrated Decision Support System for Prognostic and Diagnostic Analyses of Water Distribution System Failures. Water Resources Management, 30(8), 2831–2850. doi:10.1007/s11269-016-1326-6

[13] Islam, M. S., (2016). Comparative Evaluation of Vacuum Sewer and Gravity Sewer Systems, International Journal of Systems Assurance Engineering and Management (IJSA), Doi: 10.1007/s13198-016-0518-z (Accepted)

[12] Islam, M.S., Sadiq, R., Rodriguez, M.J., Najjaran, H., Hoorfar, M., (2014), Reliability Assessment for Water Supply Systems under Uncertainties, ASCE Journal of Water Resource, Planning and Management, 140(4), 468–479.

[11]Islam, M. S., Babel, M. S., (2013), Economic Analysis of Leakage of Bangkok Water Distribution System, ASCE Journal of Water Resource, Planning and Management, 139(6), 209-216.

[10]Islam, M. S., Sadiq, R., Rodriguez, M. J., Najjaran, H., Francisque, A., & Hoorfar, M. (2013). Evaluating Water Quality Failure Potential in Water Distribution Systems: A Fuzzy-TOPSIS-OWA-based Methodology. Water Resources Management, 27(7), 2195–2216.

[9] Zargar, A., Dyck, R., Islam, M.S., Mohapatra, A., Sadiq, R., (2014), Data Fusion Methods for Human Health Risk Assessment: Review and Application, the Journal of Human and Ecological Risk Assessment: An International Journal, 20(3), 807-838.

[8] Zhang, K, Zargar, A., Achari, G., Islam, M.S., Sadiq, R., (2014), Application of Decision Support Systems in Water Management, Journal of Environmental Review (In press), available online:  http://www.nrcresearchpress.com/doi/abs/10.1139/er-2013-0034

[7] Islam, M.S., Sadiq, R., Rodriguez, M.J., Najjaran, H., Hoorfar, M., (2013), Water Distribution System Failure: A Forensic Analysis Framework, Accepted for publication to the Journal of Environment, Systems and Decisions (In Press), and Available: http://link.springer.com/article/10.1007%2Fs10669-013-9464-3

[6] Dyck, R., Islam, M.S., Zargar, A., Mohapatra, A., Sadiq, R., (2013), Application of data fusion in human health risk assessment for hydrocarbon mixtures on Contaminated sites, Toxicology journal, 313(2-3), 160-73

[5] Islam, M.S., Zargar, A., Dyck, R., Mohapatra, A., Sadiq, R., (2012), Data Fusion-based Risk Assessment Framework: An Example of Benzene, International Journal of Systems Assurance Engineering and Management, 3 (4), 267-283

[4] Islam, M.S., Sadiq, R., Rodriguez, M.J., Francisque, A., Najjaran, H., Hoorfar, M.,(2011), Leakage Detection and Location in Water Distribution System using a Fuzzy-Based Methodology, Urban Water Journal, 9(6), 351-365, (In top 10 most read papers since 2011)

[3] Islam, M.S., Sadiq, R., Rodriguez, M.J., Francisque, A., Najjaran, H., Naser, B., Hoorfar, M., (2012), Evaluating Leakage Potential in Water Distribution Systems: A Fuzzy-Based Methodology, Journal of Water Supply: Research and Technology – AQUA, 61(4), 240–252.

[2] Babel, M. S., Islam, M. S. and Das Gupta, A., (2009), Leakage Management in a Low-Pressure Water Distribution Network of Bangkok, Water Science & Technology: Water Supply—WSTWS, 9 (2), 141–147.

[1] Islam, M. S, Pal, S. K.,  and Babel, M.S. (2007), Artificial Neural Network for Pressure Management and new Leak Detection-A Cost effective Approach, CUET Journal of Civil  and Earthquake Engineering,  1, 100-107, ISSN: 1996-9066.

 

Book Chapter


[1] Babel, M. S., Islam M. S. and A. A. Rivas (2010). Application of Hydraulic Modelling for Leakage Management in the Bangkok Water Supply System- A Case Study, In Price, R.K. and Z. Vojinovic (2010). Urban Hydroinformatics: Data, Models and Decision Support for Integrated Urban Water Management, IWA Publishing, December, 2010.

Professional Magazine

[1] Islam, M. S, Achari, G., Islam, M.S., Sadiq, R., (2014). Potential Impacts of Hydraulic Fracturing on water and environment, CSCE Canadian Civil Engineers, May 2014

Conference Publications

[8] Islam, M.S., Sadiq, R., Rodriguez, M. J., Francisque, A., Najjaran, H., Naser, B., Hoorfar, M., (2012), Water Distribution System Failure: A Forensic Analysis. Presentation at the Underground Infrastructure Research (UIR) International Conference and Road Show, Niagara Falls, Ontario, June 5-6.

[7] Islam, M.S., (2012) Economic Level of Leakage: A Cost Effective Leakage Management Tool, BCWWA Annual Conference and Tradeshow, Penticton, BC, 21-15 April, 2012

[6] Islam, M.S., Sadiq, R., Rodriguez, M. J., Francisque, A., Najjaran, H., Naser, B., Hoorfar, M., (2011a), Leakage Forensic Analysis for Water Distribution Systems: A Fuzzy-Based Methodology. Proceedings of the 20th Canadian Hydrotechnical CSCE Conference, Ottawa, Ontario, Canada, June 14-17, 2011.

[5] Babel, M. S., Islam, M. S. And A. Das Gupta (2007). Leakage Analysis and Management in a Low Pressure Water Distribution Network of Bangkok, Proceedings of 2nd IWA – ASPIRE, Conference and Exhibition (CD-ROM), Perth, Australia, 29-31 October.

[4] Islam, M. S., Babel, M. S. and Liong S.Y., (2006), Cost Effective Applications of Artificial Neural Network for Pressure Management and New Leak Detection.  Proceedings of 7th International Conference on Hydroinformatics, HIC2006, held at Nice, France, 4-8 September 2006, Volume III, pp 2016-2023.

[3] Islam, M. S., Babel, M. S. and Gupta, A. D., (2006), Application of EPANET Hydraulic Model for Leakage Reduction in Bangkok Water Distribution Network. Proceedings of 7th International Conference on Hydroinformatics, HIC2006, held at Nice, France, 4-8 September 2006, Volume IV, pp 2789-2796.

[2] Islam, M. S., Babel, M. S. and Gupta, A. D., (2005), Economic Analysis of Leakage in the Water Distribution Network of Bangkok. CD-ROM proceeding, 12th IWRA World Water Congress, 22-25 November 2005 at New Delhi, India

 [1] Islam, M. S., Babel, M. S. and Das Gupta, A., (2005), Pressure Management for Leakage Reduction in a Water Distribution Network. Proceedings of the MTERM International Conference, held at AIT, Bangkok, Thailand, 8-10 June 2005, pp 587-594.

Poster Presentations

[6] Islam, M.S., Sadiq, R., Rodriguez, M.J., Francisque, A., Najjaran, H., Naser, B., Hoorfar, M., (2012), Integrated Prognostic and Diagnostic Analysis of Water Distribution System Failures, BCWWA Annual Conference and Tradeshow, Penticton, BC, 21-15 April, 2012

[5] Islam, M.S., Sadiq, R., Rodriguez, M.J., Francisque, A., Najjaran, H., Naser, B., Hoorfar, M.,(2012), Water Distribution System Failures: An Integrated Prognostic and Diagnostic Analysis Framework, The University of British Columbia, Okanagan, School of Engineering Research Poster Competition,  March, 2012, Received Best Poster Award

[4] Mohapatra, A., Sadiq, R., Zargar, A., Islam, M.S., Dyck, R.  (2011), A review of Data Fusion Methodology and Applications in the context of Dose Response Assessment and Human Health Risk Assessment, OpenTox2011, Innovation in Predictive Toxicology: OpenTox InterAction Meeting 2011,  Technical University of Munich, Munich, Germany, 9-12 August 2011

[3] Islam, M.S., Sadiq, R., Rodriguez, M.J., Francisque, A., Najjaran, H., Naser, B., Hoorfar, M., (2010), Water Distribution System Failure: A Forensic Analysis, The University of British Columbia, Okanagan, School of Engineering Research Poster Competition ( November, 17, 2010). (was selected for final round)

[2] Dyck, R., Islam, M.S., Zargar, A., Mohapatra, A., Sadiq, R., (2010), Risk Assessment Framework for Contaminated Sites: Data Fusion Techniques, The University of British Columbia, Okanagan, School of Engineering Research Poster Competition (November, 17, 2010).

[1] Islam, M.S., Babel, M. S. and Sadiq, R.,(2010), Estimation of Economic Level of Leakage –A Cost Effective Approach, BC water Symposium, The University of British Columbia, Okanagan, Canada, August, 30, 2010.

Technical Reports

[4] Islam, M.S., (2012 Water Model Management Plan- Review and Recommendations, Prepared for City of Kelowna, Canada

[3] Islam, M.S., (2012) Sewer Model Management Plan- Review and Recommendations, Prepared for City of Kelowna, Canada

[2] Sadiq, R., Islam, M.S., Zargar, Dyck, R., (2011), Risk Assessment Framework for Contaminated Sites: A Critical Review and Potential Applications of Data Fusion Methods. Submitted to the Regions and Programs Branch (RAPB) Health Canada Health Canada, Calgary, Alberta, Canada (One of the main contributor)

[1] Janmaat, J, Islam, M.S., (2011), Review of Biophysical Impact of Columbia River Treaty Dams, Submitted to the Columbia Basin Trust, BC, Canada


Workshop Presentations

[2] Mohapatra, A., Sadiq, R., Zargar, A., Islam, M.S., Dyck, R.  (2011), Data Fusion-based Human Health Risk Assessment Framework: Illustrative Examples, Beyond Science and Decisions: From Issue Identification to Dose-Response Assessment, Workshop III: Alliance for Risk Assessment, Falls Church, VA, May 5, 2011 (One of the main contributor)

[1] Mohapatra, A., Sadiq, R., Zargar, A., Islam, M.S., Dyck, R.  (2010), Review of data fusion methodologies to integrate data from different organizational levels, Beyond Science and Decisions: From Issue Identification to Dose-Response Assessment, Workshop III: Alliance for Risk Assessment, Crystal City, VA, October 11, 12, & 13, 2010 (One of the main contributors).

Accepted Abstracts

[3] Islam, M.S., Sadiq, R., Rodriguez, M. J., Najjaran, H., Naser,B., Hoorfar, M., (2012), Quantification of Uncertainties in WSS Reliability Assessment: A Novel Methodology, Accepted for poster and proceeding publication for the 15th  National Drinking Water Conference, Kelowna, October 2012

[2] Mohapatra, A.K., Sadiq, R., Zargar, A., Islam, M.S., Dyck, R., (2011) Application of a data fusion framework to integrate toxicity data for a petroleum hydrocarbon mixture International Toxicology of Mixtures Conference, October 21-23, 2011. Arlington, Virginia. (Poster presentation)

[1] Dyck, R. Sadiq, R., Zargar, A., Islam, M.S., Mohapatra, A.K., (2011) Application of a data fusion framework to integrate toxicity data for a petroleum hydrocarbon mixture Society For Risk Analysis Annual Meeting 2011 December 4-7, 2011. Charleston, South Carolina (Oral presentation)

 

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