Informatics and Mathematical Modelling

We are experts in solving problems related to mathematical modeling, signal processing, image processing, stochastics modelling, time series, control theory applications.

We carry out modelling, simulation and visualization of applied mathematics and physics problems in the domains of agricultural production, weather models, logistics and shortest path route planning.

Typical application areas include:

  • crop models
    • disease pressure models
    • Predictive maintenance models, Structural Health Monitoring and Condition Monitoring Systems (SHM)
    • including Early Warning Systems (EWS)
    • knowledge management systems
    • Decision Support System (DSS)
    • inverse problems and data fusion
    • control theory applications
    • image processing and vision systems
    • time series and stochastic modelling
    • machine learning and intelligent systems

An example is the investigation and modelling of fertilizer dispersion in crop production, as described in the article: “Inverse Problems and Data Fusion for Crop Production Applications Targeting Optimal Growth – Fertilization”

This work in progress is a contribution to crop growth systems for planning and monitoring of farm activities and practices by farmers. The work outlines the initial findings related to modelling, simulation and visualization techniques for crop growth, specifically targeting the barley crop, such that the crop yield is optimized with respect to several parameters (e.g. high-end user value and minimum environmental impact), thus obtaining a sustainable production. The growth process optimization is based on information, including sensor-based measurements with sensor quality monitoring, from previous and the present growth season. Initially, references targeting the importance of site-specific management for obtaining the objective of yield optimization under the constraint of minimizing the environmental load is pointed to.

This is followed by key references on modelling, simulation and visualization of the crop growth process based on information on soil quality, field seeding, spraying/fertilization and environmental information in general. Finally, references to software tools, which could form the basis for an open source platform for a planning and monitoring system for optimal crop growth in multiple application areas are given. The contribution concludes with proposals of research questions to be pursued soon.

B. Kaur and R. K. A. Owusu, “Inverse Problems and Data Fusion for Crop Production Applications Targeting Optimal Growth – Fertilization,” 2015 26th International Workshop on Database and Expert Systems Applications (DEXA), Valencia, 2015, pp. 108-114, doi: 10.1109/DEXA.2015.39. https://ieeexplore.ieee.org/document/7406278?arnumber=7406278

Novitek has developed an in-house Decision Support System (DSS)including Early Warning Systems (EWS) and Structural Health Monitoring and Condition Monitoring Systems (SHM), that helps in farm decision making and also provides climate-smart agriculture support services. The DSS is a support system and knowledge management module providing i) decision making and climate-smart agriculture support services, ii) early warning systems (EWS) and indicators, iii) structural health and condition monitoring (SHM) services of equipment and devices, and iv) other related benchmarking information/data models and tools). The knowledge management (KM) module also includes a data pool resource search engine for continuous harvesting of resources in the web (e.g. weather and pest and diseases early warning systems resources) and a visual analytic service platform, and uses cloud management facilities for collecting, combining and making accessible the currently scattered data and resources for optimal interpretation and adaptation to crops and soil dynamics and composition in agriculture. For example, the SHM will lead to improvement in repairs of equipment and machinery and sensors including vehicles and tractors that are identified and conducted to avoid repairs that are conducted methodically thereby reducing unexpected and expensive breakdowns by 60-70%. And it will also provide intelligence for remote control, monitoring and performance monitoring of processes and system.

Publications

Robert Owusu    Structural Health and Condition Monitoring (SHM) Algorithms for Subsystems, Devices and Agricultural Services     (2016) 

Bipjeet Kaur ; Center for Wireless Syst. & Applic., Tech. Univ. of Denmark, Ballerup, Denmark ; Robert K. A. Owusu Inverse Problems and Data Fusion for Crop Production Applications Targeting Optimal Growth – Fertilization 26th International Workshop on Database and Expert Systems Applications (DEXA) (2015)

Robert Owusu    Rank Reduction Algorithms for Filtering and Parameter Estimation in Inverse Problems with Applications to Agribusiness Production Systems Services              March 2015                

Campbell-Tofte, J.I.A., Mølgaard, P., Josefsen, K., Abdallah, Z., Hansen, S.H., Cornett, C., Mu, H., Richter, E.A., Petersen, H.W., Nørregaard, J.C., Winther, K. , Randomized and double-blinded pilot clinical study of the safety and anti-diabetic efficacy of the Rauvolfia-Citrus tea, as used in Nigerian Traditional Medicine. Journal of Ethnopharmacology, 133: 402–411, (2011)

Owusu, R.K.A, Particle filtering and information fusion of innovative location and tracking device for GPS  hostile environments. Applied Sciences on Biomedical and Communication Technologies,  ISABEL, 1-7 pages, ISBN: 978-1-4244-2647-8, ISBN: 978-1-4244-4640-7, Current Version Published: january 2009

Owusu, R.K.A, Rank Reduction Algorithms for Filtering and Parameter Estimation in Inverse Problems with Applications, Applied Sciences in Biomedical and Communication Technologies, 2009. ISABEL 2009, 1 – 7 pages, ISBN: 978-1-4244-4640-7, Current Version Published: january 2010

Owusu, R.K.A, Robust Algorithms for Filtering and Parameter Optimization in Inverse Problems, Applied Sciences in Biomedical and Communication Technologies, 2009. ISABEL 2009, 1-10 pages, ISBN: 978-1-4244-4640-, Current Version Published: january 2010

Campbell-Tofte, J., Hansen, S. H., Mu, H., Mølgaard, Per.  Increased lipids in non-lipogenic tissues are indicators of the severity of type II diabetes in mice. Prostaglandins, Leukotrienes and Essential Fatty acids, 76: 9-1,(2007)

Campbell, J. I.A, Mortensen A., Mølgaard P.  Tissue lipid lowering-effect of a traditional Nigerian anti-diabetic infusion of Rauwolfia vomitoria foliage & Citrus aurantium fruit. Journal of Ethnopharmacology, 104: 379-386, (2006).

Nielsen, C.K., Campbell, J.I.A., Öhd, J.F., Mörgelin, M., Riesbeck, K., Landberg, G. and Colander A. (2005) A novel localization of the G-protein coupled CysLT1 receptor in the nucleus of colorectal adenocarcinoma cells. Cancer Research, 65: 732-742. 5

Öhd, J.F., Nielsen, C.K., Campbell, J., Landberg, G., Löfberg, H. and Colander, Expression of the Leukotriene D4 receptor CysLT1, COX-2, and other cell survival factors in colorectal adenocarcinomas. Gastroenterology, 124: 57-70, (2003).