BATTLE Project

1. BATTLE Project UNI EN ISO 9001 : 2000 Certif. N.9150.ANVA Research and Development in Engineering field of Knowledge and Software Applications C.5 - Expert System Design • C.5.1 – Principles and Technologies for real-time Checking & Validation Analytical Data • C.5.2 – Instrumentation & Sensor Technology Assessment • C.5.3 – Need Assessment & Solution Analysis • C.5.4 – Expert System Basic Design & Lab Prototyping • C.5.5 – “At Factory” Expert System Functional Architecture Design and Sw Implementation • C.5.6 – Support on Validation of the Expert System • C.5.7 –Expert System Hw/Sw Equipment Supplying and Integration • C.5.8 – Issue of Deliverable “Expert System Specification” Expert System Specification”

2. BATTLE Project C.5.1 - Principles and Technologies for real-time Checking & Validation Analytical Data Problem Setting 1) On-Line/Real-time monitoring of wastewater quality remains a scarcely resolved problem into the wastewater treatment industry. A water quality assessment requires of more then fifty of specific chemical and physical parameters to be properly detected, all of them on samples by off-line laboratory instrumentation. Moreover, for water reuse scope (by using membranes technologies), on-line automatic controller and regulating flow valves require process real-time data-input. 2) In spite of a deep changeability of textile segregated wastewater stream quality, there are only a few chances (instrumentation technologies) to on-line detect water quality parameters and, no one of them, it is directly correlated to a specific pollutant.

3. BATTLE Project C.5.1 - Principles and Technologies for real-time Checking & Validation Analytical Data Data Analysis / Knowledge Extraction Data Analysis & On-Line Data Mining – Analyzing Data Methods (Multivariate Analysis) – Data Inferentiation and Validation – Data Integration and Fusion Knowledge Engineering (Expert Systems) – Knowledge extraction and Formalization – Knowledge Conceptualization and Modeling – Knowledge Automation and Machine Learning (Expert Systems)

4. BATTLE Project C.5.1 - Principles and Technologies for real-time Checking & Validation Analytical Data PCA – Data Analysis

5. BATTLE Project C.5.1 - Principles and Technologies for real-time Checking & Validation Analytical Data Problem Solving • Applications of Artificial Intelligence embedded into multi-sensor or cluster sensor technology for early-warning monitoring and real-time distributed process control: • How to be able to on-line measure intangibles parameters or complex and important indicators by not specific measurements like pH, ORP, Temp., Conductivity, Torbidity, UV and so on. • How to collect and deploy data acquired and make a logical fusion in a Knowledge Modeling, to timely detect an early-warning or real-time fault diagnosis and remediation (Knowledge Base eXtraction from data acquisition system and human expertise); • How to get data acquisition system on-line self-learning from real multivariate process working events (extreme variability of the process effluents), without continuous and expensive Lab sampling and analysis

6. Expert Knowledge BATTLE Project Color Index Key Performance Indicators Probe/Sensors Organic Index IDQ Quality Index Applicable Flux Fouling Index IDF Filtration Index Remote Control Expert Node Permeate Loss Flux Loss C.5.2 – Instrumentation & Sensor Technology Assessment WPR = (dissolved salts; dissolved organic substances; total suspended solids) pH[6,5÷9]

7. BATTLE Project C.5.2 – Instrumentation & Sensor Technology Assessment

8. BATTLE Project C.5.3 - Need Assessment & Solution Analysis • The Solution: • That means to perform a continuous on-line control on the different side stream and to select the most suitable effluents streams for the next treatment, for the reuse: • Real-Time matching the extreme variability of the process effluents by mixing and/or switching their feeder with the objective of the maximisation of reuse in respect of the limits at the final discharge. • Acquiring of cluster dynamic signals have to be compared with the specific dynamic of process or event which they are referring (slow in environmental application, fast in vibration data modelling..). • knowledge engineering and modelling real-time application (from expertise, human experts, technical literature, and so on), in Artificial Neural Fuzzy Net with the innovative expert nodes for complex and heterogeneous real-time application, but also in expert systems and decision support system applications

9. BATTLE Project C.5.4 – Expert System Basic Design & Lab Prototyping SCn Monitoring Cluster Node KB RCN Remote Control Expert Node Expert System Knowledge Updating Incremental Knowledge of Process Control

10. QCP BATTLE Project SCn I/O SCn I/O P10 R1 WR12 R5 R4 R6 WR14 R2 QCP QCP QCP QCP QCP QCP QCP SCn I/O P2 P7 P8 P1 P4 P6 P5 SCn I/O SCn I/O SCn I/O SCn I/O SCn I/O SCn I/O STm2 STm3 STm1 KB/RCN1 KB/RCN2 KB/RCN3 WWTP UF QCP P11 T11 C.5.4 – Expert System Basic Design & Lab Prototyping PC Station/SQL XBASE Server Expert System - XBASE

11. BATTLE Project C.5.4 – Expert System Basic Design & Lab Prototyping ES/Control Node Matching Expert System Cognitive Map Control Expert Node Knowledge Base

12. BATTLE Project C.5.5 – “At Factory” Expert System Functional Architecture Design and Sw Implementation The Testing/Simulation System

13. BATTLE Project Dati Macchinario SCn KB/RCN Comandi Contatto Pompa Aggiorna Server Dati Elaborazione Supervisiona/corregge Palmare C.5.6 - Support on Validation of the Expert System

14. BATTLE Project C.5.7 -Expert System Hw/Sw Equipment Supplying and Integration

15. BATTLE Project C.5.8 – Issue of Deliverable “Expert System Specification” See deliverable.