Decision Support Technologies
The analysts and engineers in the Automation and Data Systems Division at Southwest Research Institute (SwRI) are developing and applying advanced methodologies and techniques that extend the disciplines of predictive analytics, data mining, and business intelligence.
The focus of our Decision Support expertise is to go beyond the capabilities offered by commercially available software packages in these disciplines and analyze current and historical facts to make predictions about future events, thereby facilitating the decision-making process. This analysis involves the extraction of information from large and disparate data sets typically found in large enterprises by applying structure and context, such as organizing the data into a data warehouse. This information can then be analyzed by subject matter experts to classify the underlying meaning contained in the information, resulting in knowledge applicable to the client business processes. From that knowledge, attributes such as historical trends, indicators, and dependencies can be exposed to reveal non-intuitive aspects of those business processes, producing wisdom from the applied insight. Then, decisions regarding actions, based upon direction and principles, are formulated to facilitate the needs of the client.
SwRI has been intimately involved in a wide variety of decision support related projects, such as:
- Adverse drug effects
- Alternate dispute resolution
- Chemical process reporting
- Advanced visualizations
- Reversible lane transportation systems
- Traffic management
- Smart grid
To support the safe and profitable operation of reversible lane transportation systems, data such as event monitoring, incident detection, and traffic density are used to influence decisions regarding traffic directional changes, gate and barrier opening/closing, and tolling rates.
Using patient related data such as lab values and medication orders, trending reports can be generated to visualize adverse drug effects used to improve the underlying rule-based triggering mechanisms.
Using smart phone sensing capabilities, such the built-in accelerometer and magnetometer, data analysis techniques can be used to make decisions based upon vehicle movement and intra-vehicle location.
intelligent systems • project trends