Grant: Alliance Grants
University of Regina
$127,500.00
Public Safety and Trust Based Systems
EF 2021-22
Résumé
This project will apply computer science and data science in novel and effective ways to address public safety problems managed by the Saskatchewan Ministry of Corrections, Policing, and Public Safety ("the Ministry"). The core activity of the Ministry is to oversee Saskatchewan's correctional system and facilities, and to provide guidance and support to Saskatchewan's municipal police services. Specifically, the goals of this project are to (A) improve monitoring of the inmate telephone system ("Telmate") by increasing the speed and decreasing the cost of transcribing inmate calls, (B) improve the monitoring of the same system by detecting anomalous patterns of usage, and (C) estimating the trustworthiness of computerized agents. The potential outcomes, besides the research results themselves, are new policies and procedures for the Ministry. As examples: (A) more convenient transcription of telephone calls may allow security intelligence officers to change their procedures for analyzing security threats by allocating more time to analysis and less to listening, (B) detailed analysis of telephone call log data may lead to policies affecting the permissible frequency, duration, and times of inmate calls, and (C) improved understanding of trust in automated systems may contribute to the future formulation of new policies for automated vehicles. The primary benefit will be to aid the Ministry in several initiatives related to public safety in Saskatchewan. The project is intended to increase public and inmate safety by detecting illegal behaviours, facilitating the analysis of confidential data, and reducing the errors made by automated systems. It will also provide training for highly qualified personnel in computer science, data science, software design, data mining, database access, speech recognition, trust-based protocols, machine learning, deep learning, time series, and handling private information.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Saskatchewan, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
561135-2020
Name nom
Hamilton, Howard
Department département
Computer Science
Organization id
17
Institution établissement
University of Regina
Province en
Saskatchewan
Province fr
Saskatchewan
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2021
Competition year année de concours
2020
Award amount
127500
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
802
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information systems and technology
Area of application fr
Systèmes d'information et technologie de l'information
Research subject code
2705
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Software and development
Research subject fr
Logiciels et développement
Installment
inst:1
Partie
1
Nb partie
2
Application title
Public Safety and Trust Based Systems
Keyword
NSERC
Application summary
This project will apply computer science and data science in novel and effective ways to address public safety problems managed by the Saskatchewan Ministry of Corrections, Policing, and Public Safety ("the Ministry"). The core activity of the Ministry is to oversee Saskatchewan's correctional system and facilities, and to provide guidance and support to Saskatchewan's municipal police services. Specifically, the goals of this project are to (A) improve monitoring of the inmate telephone system ("Telmate") by increasing the speed and decreasing the cost of transcribing inmate calls, (B) improve the monitoring of the same system by detecting anomalous patterns of usage, and (C) estimating the trustworthiness of computerized agents. The potential outcomes, besides the research results themselves, are new policies and procedures for the Ministry. As examples: (A) more convenient transcription of telephone calls may allow security intelligence officers to change their procedures for analyzing security threats by allocating more time to analysis and less to listening, (B) detailed analysis of telephone call log data may lead to policies affecting the permissible frequency, duration, and times of inmate calls, and (C) improved understanding of trust in automated systems may contribute to the future formulation of new policies for automated vehicles. The primary benefit will be to aid the Ministry in several initiatives related to public safety in Saskatchewan. The project is intended to increase public and inmate safety by detecting illegal behaviours, facilitating the analysis of confidential data, and reducing the errors made by automated systems. It will also provide training for highly qualified personnel in computer science, data science, software design, data mining, database access, speech recognition, trust-based protocols, machine learning, deep learning, time series, and handling private information.