Mobile Application and Public Safety System for Crime Tip-Off and crime prevention by communities

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1 Mobile Application and Public Safety System for Crime Tip-Off and crime prevention by communities By Dr. Keeratpal Singh, Principal Engineer, MIMOS Berhad Senior Assistant Commissioner Dato' Aishah binti Mohammad, Principal Assistant Director, Management Department, Royal Malaysia Police 10 th to 11 th June 2014

2 Content of Presentation *MIMOS is research and technology collaboration partner for PDRM* PDRM (Royal Malaysia Police) MIMOS (Malaysia s R&D center for ICT) Introduction and Abstract of Paper Rakan Cop Initiative and statistics on Rakan Cop Necessity of Community Engagement SMS and Smart Phone Applications for Crime Prevention Features of Applications Public Safety Server System & Complaints routing Big for Crime Analytics Big Related Research and Platforms by MIMOS Q&A 2

3 Abstract and Introduction In order to reduce crime, community engagement is a necessity. The usage of mobile phones is increasing from basic SMS applications, to snapping photos and sending via multimedia applications, using social media application, and using specific smart phone applications intended for community needs. The application for SMS would be on the server of the Public Safety System, where people could send crime tip-off to a specific short code phone number via short message. The server would send back to the user(s) some SMS questions to be interactively answered by user. For users with smart phones, a community specific smart phone application (such as for IOS and Android) could be downloaded from the information provided via the public safety web site. 3

4 Abstract and Introduction The application enables chatting with public safety officers, filling in the tip-off form, submitting via the mobile application and also uploading photos relevant to the tip-off. The public safety server system is intended to: store, route the tipoff to the officer(s), track the jobs assigned to the officer(s), update the community user who had provided the tip-off, update and report to relevant authorities. Complaints such as dark and quiet areas due to damaged street lights and damaged public and emergency phones, will be routed by the system to engage relevant governmental/private authorities to make necessary repairs before tasks are flagged as resolved. The Public Safety Server System will utilize big data processing using Hadoop Distributed File System (HDFS) for further Crime Analytics. 4

5 Royal Malaysia Police The main function of the Royal Malaysia Police (RMP) or also known as Polis Di Raja Malaysia (PDRM) is: To maintain Law and Order To maintain peace and safety of Malaysia To prevent and detect crime To arrest and prosecute offenders To gather security intelligence 5

6 Royal Malaysia Police Org Chart Head of Police Malaysia Inspector General of Police Deputy Head of Police Malaysia Deputy Inspector General of Police Management Department Criminal Investigation Department Special Branch Internal Security and Public Order Department Commissioner of Police Commissioner of Police Commissioner of Police Commissioner of Police Logistics Department Commercial Crimes Investigation Department Narcotics Criminal Investigation Department Crime Prevention and Community Safety Department Commissioner of Police Commissioner of Police Commissioner of Police Commissioner of Police

7 MIMOS: An Overview Unit under the Prime Minister s Department: R&D in ICT and Microelectronics R&D to drive development of indigenous ICT industry A Department under the Ministry of Science, Technology and the Environment: emphasis on R&D and assumed role in IT policy development MIMOS Berhad was formed, as a MoF Incorporated Company Mandates: R&D in ICT & Microelectronics Business Development National ICT Policy Secretariat Present New mandate: To focus on: R&D in ICT & Microelectronics for national industry competitiveness Enhancing eco-system for E&E industry Generating New Technology Ventures and Incubating Industry 7

8 Cluster Landscape 8

9 Cluster Landscape NANOELECTRONICS PHOTONICS ADVANCED ANALYSIS & MODELING MICRO-ELECTRONICS /ENERGY KNOWLEDGE TECHNOLOGY INTELLIGENT INFORMATICS PSYCHOMETRICS ADVANCED COMPUTING ACCELERATIVE TECHNOLOGY WIRELESS COMMUNICATIONS INFORMATION SECURITY 9

10 IP Growth April (as at 25 th April 2014)

11 IP: National Performance No. Malaysian Applicant Total 1 MIMOS BERHAD UNIVERSITI MALAYA UNIVERSITI TEKNOLOGI MALAYSIA 87 4 TELEKOM MALAYSIA BERHAD 64 5 UNIVERSITI PUTRA MALAYSIA 62 6 UNIVERSITI TEKNOLOGI PETRONAS 61 7 UNIVERSITI MALAYSIA PAHANG 35 8 UNIVERSITI KEBANGSAAN MALAYSIA 30 9 MALAYSIAN PALM OIL BOARD INSTITUTE OF TECHNOLOGY PETRONAS SDN BHD 25 TOP patent filer in

12 PCT Patent Filings We Are In Top 10 Source: WIPO 2013 PCT Yearly Review 12

13 Software Engineering Institute (SEI) Capability Maturity Model Integrated Level 5 13

14 Rakan Cop Rakancop (Friends of the Police) SMS e-community won the Prime Minister's Best of the Best Award, the top award at the MSC Malaysia Asia Pacific ICT Alliance (APICTA) 2009 awards at the Putra World Trade on the evening of 8 October SMS to Register with Police and assist the police to reduce crime. Approximately 563K members and about 11 new members a day (2 nd June 2014) SMS to Police when you are leaving for holidays. Source from: Rakan Cop Website and FB 14

15 Index Crime Cases for PDRM from ,000 Total INDEX Crime from , , , , ,000 Rakan Cop 177, , , , ,000 50,000 Crime prevention activities and necessity of community engagement such as Rakan Cop, meeting and greeting community are some of the factors that reduces the overall Index cases

16 Smart Phone usage increasing: need multi-channel community reach using smart phone apps with social network integration Features to add from SMS based tipping user user user cop cop Public Safety System: 1.)Cops Web based admin 2.)KPI dashboard for problems and complaints 3.)Job tracking 4.)link to social media 5.)Secured chats Interactive SMS application on the server of the Public Safety System, where people could send crime tip-off to a specific short code phone number via SMS and server would send back to the user(s) some SMS questions to be interactively answered by user. For users with smart phones, a community specific smart phone application (such as for IOS and Android) could be downloaded from the information provided via the public safety web site for: Chatting with public safety officers, Filling in the tip-off form, submitting via the mobile application Uploading photos relevant to the tip-off. Snapping photos and sending via multimedia applications and through social media application Providing specific smart phone applications intended for community needs. Reserved. 16

17 Public Safety System Crime Analytics The public safety server system is intended to: Store data as RDBMS or HDFS and Task tracking Linking to Social Media and other unstructured data Provide secure, community based locations, broadcast and public chats Provide Rating based on historical data and clustering tippers creditability Web Admin for RMP and KPI Dashboards for Community suggestions and issues Route the tip-off and issues to the available officer(s) Track the job status assigned to the officer(s) Update the community user who had provided the tip-off Update and report to relevant authorities. Complaints such as dark and quiet areas due to damaged street lights and damaged public and emergency phones, will be routed by the system to engage relevant governmental/private authorities to make necessary repairs. The Public Safety Server System will utilize big data processing using Hadoop Distributed File System (HDFS) for further Crime Analytics. Reserved. 17

18 Value of from RMP (PDRM) Mi-Helio, Mi-Accstats and Mi-BIS (MIMOS Platforms) Integrated solution for Public Safety System Structured UnStructured SafeCity Management System Station Management System PDRM HRMIS Police Reporting System GPS Reserved.

19 MIMOS Accelerated Statistics (Mi-AccStats) Crime Prevention and Communities 11 th June 2014 Current Problem: With data emerging to Terabytes and Petabytes, it is very tedious to perform complex statistical analysis and visualize the key performance indicators of variables being measured in real time. With Mi-AccStats, analysts can make statistical-driven decisions and visualize analytics on almost real time for big data that impact their performance with easy-to-use statistical libraries and web tools. Overview MIMOS Mi-AccStats enables the processing of statistical analysis on big data consisting of structured or unstructured data. Along with Mi-BIS, businesses could easily create reports, perform in-depth statistical analysis which includes data exploration, analysis, plotting and visualisation of multi-dimensional data. Features: -Analytic Component Built-in statistical tools for analytic, statistical and predictive analysis using accelerated parallel algorithm and GPGPU -Processing Component Capabilities to process structured and unstructured terabytes and petabytes of data processing using Map Reduce, Hadoop, accelerated parallel mechanism and GPGPU libraries. -Dashboard Management through Web, Mi-BIS or other Vendor s BI Support various type of business intelligence (BI) tools with dashboard to support user requirements for data analysis and decision making. Technology Benefits: -Accelerate Processing Libraries and middleware to support big data with statistical analysis and visual analytics -Gain New Insights Built-in ad hoc query capabilities of Mi-BIS with Mi-AccStats allow users to get instantaneous results, view statistical plots, and strengthen their understanding of the underlying business patterns resulting in new insights into the dynamics that lead to performance analysis of variables being analysed. -Easy to Integrate Could be integrated with Mi-BIS or any BI tool Powered By MIMOS ATL (Accelerated Technology Lab) 2014

20 Mi-BIS (with Big ) - Predictive Analytics 20

21 Mi-BIS (with Big ) for Video Surveillance analytics 21

22 Variety of Unstructured 22 Reserved.

23 Unstructured Collector Mi-Clip Harvesting Extracting Value from by MIMOS Communicating Status Mi-IDS Cleansing Linking to EXTERNAL SERVICES Mi-ESB Anonymisation Sharing Staging UnStructured Sources Structured Sources Cleansing Correction Detect Correction Exception Mi-Morphe + Mi-AccLib Terminologies Mi-Semantics Scrambled database & marts Anonymisation Mi-Scrambler + Mi-Crypto on the GO Mi-Mobile Value Extraction Document Repository Mi-DOC Authentication & Authorization Mi-UAP Mi-ARMC Warehouse Platform Mi-DW Solution Granular Primary base Published Marts Modeling Visualization Mi-HELIO Analytics Mi-BIS Decision Support System Mi-DSS Statistics Mi-AccStat Virtualized Platform & Integrity Manager Mi-CLOUD + Mi-Trust 23

24 Unstructured Collector Mi-Clip Harvesting Extracting Value from Communicating Status Mi-IDS Cleansing Linking to EXTERNAL SERVICES Mi-ESB Anonymisation Sharing Staging UnStructured Sources Structured Sources Cleansing Correction Detect Correction Exception Mi-Morphe + Mi-AccLib Terminologies Mi-Semantics Scrambled database & marts Anonymisation Mi-Scrambler + Mi-Crypto on the GO Mi-Mobile Value Extraction Document Repository Mi-DOC Authentication & Authorization Mi-UAP Mi-ARMC Warehouse Platform Mi-DW Solution Granular Primary base Published Marts Modeling Visualization Mi-HELIO Analytics Mi-BIS Decision Support System Mi-DSS Statistics Mi-AccStat Virtualized Platform & Integrity Manager Mi-CLOUD + Mi-Trust 24

25 Unstructured Collector Types of Mi-Clip Beyond Keywords Natural Language Processing Structured Sources Staging UnStructured Sources to be harvested GPS 25

26 Unstructured Collector Mi-Clip Harvesting Extracting Value from Communicating Status Mi-IDS Cleansing Linking to EXTERNAL SERVICES Mi-ESB Anonymisation Sharing Staging UnStructured Sources Structured Sources Cleansing Correction Detect Correction Exception Mi-Morphe + Mi-AccLib Terminologies Mi-Semantics Scrambled database & marts Anonymisation Mi-Scrambler + Mi-Crypto on the GO Mi-Mobile Value Extraction Document Repository Mi-DOC Authentication & Authorization Mi-UAP Mi-ARMC Warehouse Platform Mi-DW Solution Granular Primary base Published Marts Modeling Visualization Mi-HELIO Analytics Mi-BIS Decision Support System Mi-DSS Statistics Mi-AccStat Virtualized Platform & Integrity Manager Mi-CLOUD + Mi-Trust 26

27 Detect Correction Exception Mi-Morphe + Mi-AccLib Integrity of 10+ Million Records of transaction data Questionable data Employee_Name Improved Analytical Integrity Mi-AccLib Accelerate d & Parallelized Algorithms Valid_Reference_Name Verify Status Algorithms Used In Combination DORIS LEE CHONG LENG DORIS LEE CHONG LENG Y Exact Match NOORLAILY BT SAMSUDEE NOORAILY BINTI SAMSUDEE Y Subtracted Match Perkeso X JPN 350 Trillion X 7711 Rules combinations/rule 2.7 Quintillion Operations MAU BOO BT DASTAGIR MAU BOO BEE BINTI DASTAGI Y Levenshtein Ratio ABDILLAH B HJ RASOL ABDULLAH BIN Y WCSnd & WCLR ABDUL RASOL & FLName Algo SHU QIN TAN TAN SHU QIN Y Words Order SUZIE ARIANTI BT YASIN LEE KWAI MOY Y System Assisted Manual Verification National Sovereignty Localisation Speed of Processing 27

28 Detect Correction Exception Mi-Morphe + Mi-AccLib Velocity General Purpose GPU 28

29 ALL LEVELS Seconds ANY 3 LEVELS Detect Correction Exception Mi-Morphe + Mi-AccLib Velocity Mi-AccLib Rapid Modeling via Mi-AccLib Scheme ID Date Currency B.Entity ISIN/Security Portfolio Product ID Product Class Industry/Sector Country Strategy Dealer Credit Risk Maturity Band Up to 700 million records x s Performance 124s > 24 HOUR!! 366s 3 Levels 11 Levels (Complex) CPU GPU 29

30 Unstructured Collector Mi-Clip Harvesting Extracting Value from Communicating Status Mi-IDS Cleansing Linking to EXTERNAL SERVICES Mi-ESB Anonymisation Sharing Staging UnStructured Sources Structured Sources Cleansing Correction Detect Correction Exception Mi-Morphe + Mi-AccLib Terminologies Mi-Semantics Scrambled database & marts Anonymisation Mi-Scrambler + Mi-Crypto on the GO Mi-Mobile Value Extraction Document Repository Mi-DOC Authentication & Authorization Mi-UAP Mi-ARMC Warehouse Platform Mi-DW Solution Granular Primary base Published Marts Modeling Visualization Mi-HELIO Analytics Mi-BIS Decision Support System Mi-DSS Statistics Mi-AccStat Virtualized Platform & Integrity Manager Mi-CLOUD + Mi-Trust 30

31 Harmonizing the Terminologies Mi-Semantics Multiple Terminologies Harmonizing Eg. Healthcare Patient Name = Nama Pesakit = Pat. Name Symptoms = Tanda-tanda = Disorder Gender = Jantina = Sex Fatigue = Letih = Tiredness Acute asthma = Lelah = Acute bronchitis 31

32 Unstructured Collector Mi-Clip Harvesting Extracting Value from Communicating Status Mi-IDS Cleansing Linking to EXTERNAL SERVICES Mi-ESB Anonymisation Sharing Staging UnStructured Sources Structured Sources Cleansing Correction Detect Correction Exception Mi-Morphe + Mi-AccLib Terminologies Mi-Semantics Scrambled database & marts Anonymisation Mi-Scrambler + Mi-Crypto on the GO Mi-Mobile Value Extraction Document Repository Mi-DOC Authentication & Authorization Mi-UAP Mi-ARMC Warehouse Platform Mi-DW Solution Granular Primary base Published Marts Modeling Visualization Mi-HELIO Analytics Mi-BIS Decision Support System Mi-DSS Statistics Mi-AccStat Virtualized Platform & Integrity Manager Mi-CLOUD + Mi-Trust 32

33 Building the Marts Anonymisation Mi-Scrambler + Mi-Crypto Warehouse Platform Mi-DW Solution Modeling Encrypting Fields for anonymity Protection for sharing Granular Primary base Establishing the mart for modeling Scrambled database & marts LAWS OF MALAYSIA ACT 709 PERSONAL DATA PROTECTION ACT

34 Unstructured Collector Mi-Clip Harvesting Extracting Value from Communicating Status Mi-IDS Cleansing Linking to EXTERNAL SERVICES Mi-ESB Anonymisation Sharing Staging UnStructured Sources Structured Sources Cleansing Correction Detect Correction Exception Mi-Morphe + Mi-AccLib Terminologies Mi-Semantics Scrambled database & marts Anonymisation Mi-Scrambler + Mi-Crypto on the GO Mi-Mobile Value Extraction Document Repository Mi-DOC Authentication & Authorization Mi-UAP Mi-ARMC Warehouse Platform Mi-DW Solution Granular Primary base Published Marts Modeling Visualization Mi-HELIO Analytics Mi-BIS Decision Support System Mi-DSS Statistics Mi-AccStat Virtualized Platform & Integrity Manager Mi-CLOUD + Mi-Trust 34

35 Consumption Visualization Mi-HELIO Analytics Mi-BIS on the GO Mi-Mobile Reports Statistics Mi-AccStat Decision Support System Mi-DSS Mobile Decision Support Systems Mediums & Methods for Consumption Mi-BIS, Business Intelligence 35

36 Big Processing and Crime Analytics 1.)Demo of Big : Airlines in the USA with 123 million and 1.23 billion records on HDFS processed and viewed as below 2.)Correlation plots could be used 3.)Regression with map reduce for big data related to crime reported and crime prevention. 36

37 Thank You For more information contact: Dr. Keeratpal Singh

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