公开(公告)号：WO2015084154A1

公开(公告)日：2015-06-11

申请号：PCT/MY2014/000195

申请日：2014-06-26

Applicant: MIMOS BERHAD

Inventor： SINGH, Keeratpal ,  AFFIZA FAZREEN BINTI MOHD APAN

IPC: H04W64/00

CPC classification number: H04W64/00 ,  G01S5/02 ,  G01S5/0252

Abstract: The present invention relates to a system and method for locating a mobile device. More particularly, the invention relates to a system and method for locating a mobile device by using heterogeneous neural network. The system comprises of at least one mobile device (10), a mobile enterprise platform (20) and at least one telecommunication service provider (30). The mobile enterprise platform (20) further includes a location server (21), a database (22), a Phone Listener Application (23), a Collector Application (24) and a Quality of Positioning (QOP) Mapper (25).

Abstract translation: 本发明涉及一种用于定位移动设备的系统和方法。 更具体地，本发明涉及一种通过使用异质神经网络来定位移动设备的系统和方法。 系统包括至少一个移动设备（10），移动企业平台（20）和至少一个电信服务提供商（30）。 移动企业平台（20）还包括位置服务器（21），数据库（22），电话听众应用程序（23），收件人应用程序（24）和定位质量（QOP）映射器（25）。

公开(公告)号：WO2016012903A1

公开(公告)日：2016-01-28

申请号：PCT/IB2015/055343

申请日：2015-07-15

Applicant: MIMOS BERHAD

Inventor： SINGH, Keeratpal ,  KARUPPIAH, Ettikan Kandasamy ,  MAT NOR, Fazli

IPC: G06F17/30

CPC classification number: G06F17/30545 ,  G06F17/30477

Abstract: A system (100) and a method for querying heterogeneous data sources have been disclosed. The system (100) based on machine learning and classification rules, predicts a best route for querying at least one data source from the heterogeneous data sources. The system (100) minimizes inefficient use of hardware resources and obtains near real time response from the data source selected through the predicted route for executing the query.

Abstract translation: 已经公开了一种用于查询异构数据源的系统（100）和方法。 基于机器学习和分类规则的系统（100）预测了用于从异构数据源查询至少一个数据源的最佳路由。 系统（100）最小化硬件资源的低效率使用，并且通过用于执行查询的预测路由选择的数据源获得接近实时的响应。

公开(公告)号：WO2015088318A1

公开(公告)日：2015-06-18

申请号：PCT/MY2014/000168

申请日：2014-06-05

Applicant: MIMOS BERHAD

Inventor： SINGH, Keeratpal ,  KARUPPIAH, Ettikan Kandasamy

IPC: G06Q10/06

CPC classification number: G06Q10/0631

Abstract: Simulation model based on aggregating multi factor man power requirements of distributed geographical location needs for police which are identifiable from kea area indicators. System (100) comprising Data Extractora (104) for extracting various data sources and Categorizer for categorizing said data sources; Data Aggregator (106) for aggregating resources through multi factor causes; Simulator and Parameter Control (108); Distributor and Statistical Filter (110) for generating DS and Heat Map colours; and Colour Selector and Mapping (112) for selecting colour and mapping to redeploy and allocate resources to different geographical area boundaries with different needs. Methodology comprising steps of extracting and categorizing various data sources (302); aggregating resources through multi factor causes (304); simulating and generating processes; generating Statistical Distributor (DS) and Heat Map colours (308); and selecting colour and mapping to redeploy and allocate resources to different geographical area boundaries with different needs (310). Extracts various data sources, categorize and aggregate resources through multi factor causes, simulated effects, weightage and feedback by using simulation model, aggregation formulation and parameter controls to evaluate the performance indicators such as crime to resource ratio. Further, geographical areas are identified by providing knowledge base to distribute resources via multi factor simulation model by utilizing a Simulator Engine and heat map display generated by utilizing Distributor and Statistical Filters to effectively redeploy, allocate and distribute resources to different geographical area boundaries with different and unique needs.

Abstract translation: 基于从kea区域指标可识别的警察分布式地理位置需求的多因素人力要求聚合的模拟模型。 系统（100）包括用于提取各种数据源的数据提取（104）和用于对所述数据源进行分类的分类器; 数据聚合器（106），用于通过多因素原因聚合资源; 模拟器和参数控制（108）; 分布器和统计滤波器（110），用于生成DS和热图颜色; 和颜色选择器和映射（112），用于选择颜色和映射以重新部署并将资源分配到具有不同需求的不同地理区域边界。 方法包括以下步骤：提取和分类各种数据源（302）; 通过多因素聚合资源（304）; 模拟和生成过程; 生成统计分布器（DS）和热图颜色（308）; 并选择颜色和映射来重新部署和分配不同地理区域的资源（310）。 提取各种数据源，通过多因素原因，模拟效应，权重和反馈，通过使用模拟模型，汇总制定和参数控制对资源进行分类和汇总，以评估犯罪与资源比率等绩效指标。 此外，通过使用模拟引擎和利用分销商和统计过滤器生成的热图显示，通过多因素模拟模型提供知识库来分配资源，从而有效地将资源重新部署，分配和分配到不同的地理区域边界，通过不同的和 独特的需求。