Multi-robot-based intelligent security system

This article describes a multiple security module-based intelligent security system that has multiple communication interfaces which can be applied in home automation. The interfaces of the intelligent security system contain wired RS485, wireless RF, and Internet. The detection modules of the system have both active and passive security modules. The passive security modules contain wired security modules and wireless security modules. The control unit of all security modules is a HOLTEK microchip. Each security module has two different interfaces. They use voice modules to alarm users of an event, and to transmit real-time event signals to the supervising computer via the wired RS485 or wireless RF interface. If an event occurs, the supervising computer calculates its belief values using Dempster-Shafter evidence theory according to the passive wired and wireless security modules. If the belief value is over a set threshold, the supervising computer commands the mobile robot to move to the event location, and receives a signal from the mobile robot via the wireless RF interface. The supervising computer recognizes the final decision output using Dempster-Shafter evidence theory, and displays the detection and decision output values on the monitor of the user interface. Finally, we present some experimental results using wired passive security modules, wireless passive security modules, and active security modules for fire detection and gas leakage detection using the experimental platform of the intelligent security system.     

Multilevel multisensory-based security system for an intelligent home

This article describes a multilevel multisensor-based security system that has multiple interfaces to be applied in an intelligent home. The security system contains four levels. There is a passive detection level, an active detection level, a system supervising level, and a remote supervising level. The control unit of these passive modules is a HOLTEK microchip. Each passive module has two different interfaces (wireless RF and voice). These modules can use a voice to alarm users than an event has occurred, and can transmit the real-time status and image signal to the active detection level and the system’s supervising level via the wireless RF interface. The active detection level can communicate with other levels via the wireless RF interface or the wireless Internet. The remote supervising level, the supervising level, and the active detection level can communicate with other levels via the wireless Internet. The status of these modules can also be displayed on the monitor of the supervising computer. Finally, we present some experimental results using passive and active detection modules in the security system.     

Path planning of fire-escaping system for intelligent building

We present the path-planning techniques of the fire-escaping system for intelligent building, and use multiple mobile robots to present the experimental scenario. The fire-escaping system contains a supervised computer, an experimental platform, some fire-detection robots and some navigation robots. The mobile robot has the shape of a cylinder, and its diameter, height and weight are 10?cm, 15?cm and 1.5?kg, respectively. The mobile robot contains a controller module, two DC servomotors (including drivers), three IR sensor modules, a voice module and a wireless RF module. The controller of the mobile robot acquires the detection signals from reflective IR sensors through I/O pins and receives the command from the supervised computer via wireless RF interface. The fire-detection robot carries the flame sensor to detect fire sources moving on the grid-based experiment platform, and calculates the more safety escaping path using piecewise cubic Bezier curve on all probability escaping motion paths. Then the user interface uses A* searching algorithm to program escaping motion path to approach the Bezier curve on the grid-based platform. The navigation robot guides people moving to the safety area or exit door using the programmed escaping motion path. In the experimental results, the supervised computer programs the escaping paths using the proposed algorithms and presents movement scenario using the multiple smart mobile robots on the experimental platform. In the experimental scenario, the user interface transmits the motion command to the mobile robots moving on the grid-based platform, and locates the positions of fire sources by the fire-detection robots. The navigation robot guides people leaving the fire sources using the low-risk escaping motion path and moves to the exit door.     

Develop a multi-detection security system using multi-sensor fusion algorithms

The paper develops the multi-detection system using multi-level surveillance structure. The system contains active detection modules, passive detection modules, a supervised computer, an image system and an intelligent home. The passive detection modules contain wire/wireless detection modules and appliance control modules, and decide the event to be true or not using fusion algorithms, and transmit detection signals to the supervised computer via wire/wireless interface. Mobile robots are active detection modules and carry various sensors to search dangerous events. Each mobile robot transmits the real-time event signal to the supervised computer and the other mobile robots via wireless RF interface. The image system detects fire source using Otsu algorithm. The system integrates wire/wireless passive detection modules, mobile robots and image system to detect fire source using weighted average method. If the fire event occurs, the supervised computer calculates the dangerous grade using logical filter method according to the signals of detection modules in the first step, and transmits the position of the fire event to the other mobile robots. The assigned mobile robots move to the event location for double check autonomously, and transmit the detection results to the supervised computer. The supervised computer gives the final decision according to the feedback signals in the second step. Finally, we present some experimental scenarios using passive detection modules, active detection modules and image system for the fire detection in the intelligent home.     

Motion planning for mobile robots using a laser range finder

We have designed a mobile robot with a distribution structure for intelligent life space. The mobile robot was constructed using an aluminum frame. The mobile robot has the shape of a cylinder, and its diameter, height, and weight are 40 cm, 80 cm, and 40 kg, respectively. There are six systems in the mobile robot, including structure, an obstacle avoidance and driving system, a software development system, a detection module system, a remote supervision system, and others. In the obstacle avoidance and driving system, we use an NI motion control card to drive two DC servomotors in the mobile robot, and detect obstacles using a laser range finder and a laser positioning system. Finally, we control the mobile robot using an NI motion control card and a MAXON driver according to the programmed trajectory. The mobile robot can avoid obstacles using the laser range finder, and follow the programmed trajectory. We developed the user interface with four functions for the mobile robot. In the security system, we designed module-based security devices to detect dangerous events and transmit the detection results to the mobile robot using a wireless RF interface. The mobile robot can move to the event position using the laser positioning system.     

Detection system of a security robot using multisensor fusion algorithms

This article develops a detection system with a module-based intelligent security robot that has a uniform interface. The detection system contains a power detection module, a gas detection module, an environment detection module, and a fire detection module, etc. The control unit of these modules is a HOLTEK microchip. These modules can communicate with a master module via an I2C interface. The master module communicates with the main controller of the security robot via an RS232 interface. The main controller of the security robot system is an industry personal computer (IPC). It can display the status of these modules on the monitor. These detection modules can enhance the detection results using multisensory fusion algorithms. The user can add or remove the detection modules in any time, and the main controller can acquires sensor signals from these detection modules in real-time. Finally, we present some experimental results using these detection modules, and integrate these modules in a module-based intelligent security robot that executes several scenarios.     

Speech-based formation control of the multi-robot system

The article presents multiple pattern formation control of the multi-robot system using A* searching algorithm, and avoids the collision points moving on the motion platform. We use speech recognition algorithm to decide the various pattern formations, and program mobile robots to present the movement scenario on the grid-based motion platform. We have been developed some pattern formations to be applied in game applications, such as long snake pattern formation, phalanx pattern formation, crane wing pattern formation, sword pattern formation, cone pattern formation and so on. The mobile robot contains a controller module, three IR sensor modules, a voice module, a wireless RF module, a compass module, and two DC servomotors. The controller of the mobile robot can acquire the detection signals from reflect IR sensor modules and the compass module, and decide the cross points of the aisle. The mobile robot receives the command from the supervised computer, and transmits the status of environment to the supervised computer via wireless RF interface. We develop the user interface of the multi-robot system to program motion paths for various pattern formation exchanges using the minimum displacement. Users can use speech to control the multiple mobile robots to execut pattern formation exchange. In the experimental results, users can speak the pattern formation. The speech recognition system receives the signal to decide the pattern formation. The multiple mobile robots can receive the pattern formation command from the supervised computer, and arrange the assigned pattern formation on the motion platform, and avoid other mobile robots.     

Developing a vision-based auto-recharging system for mobile robots

This article describes a vision-based auto-recharging system that guides a mobile robot moving toward a docking station. The system contains a docking station and a mobile robot. The docking station contains a docking structure, a control device, a charger, a safety detection device, and a wireless RF interface. The mobile robot contains a power detection module (voltage and current), an auto-switch, a wireless RF interface, a controller, and a camera. The controller of the power detection module is a Holtek chip. The docking structure is designed with one active degree of freedom and two passive degrees of freedom. For image processing, the mobile robot uses a webcam to capture a real-time image. The image signal is transmitted to the controller of the mobile robot via a USB interface. We use an Otsu algorithm to calculate the distance and orientation of the docking station from the mobile robot. In the experiment, the proposed algorithm guided the mobile robot to the docking station.     

Path planning of a multiple mobile robot system

We present path-planning techniques for a multiple mobile robot system. The mobile robot has the shape of a cylinder, and its diameter, height, and weight are 8 cm, 15 cm, and 1.5 kg, respectively. The controller of the mobile robot is an MCS-51 chip, and it acquires detection signals from sensors through I/O pins. It receives commands from the supervising computer via a wireless RF interface, and transmits the status of the robots to the supervising computer via a wireless RF interface. The mobile robot system is a module-based system, and contains a controller module (including two DC motors and drivers), an obstacle detection module, a voice module, a wireless RF module, an encoder module, and a compass detection module. We propose an evaluation method to arrange the position of the multiple mobile robot system, and develop a path-planning interface on the supervising computer. In the experimental results, the mobile robots were able to receive commands from the supervising computer, and to move their next positions according to the proposed method.     

基于Linux操作系统的智能家居管理方案

物联网的兴起为智能家居提供了条件。本文提出了一种可行的智能家居的实现方法,通过2.4GHz的无线射频收发芯片nRF24L01完成内部家居终端联网,并与主控平台通信。通过西门子公司的MC39iGSM/GPRS终端无线模块实现与外网通信。整个主控平台由S3C2440作为主控芯片并基于嵌入式Linux操作系统开发,具有友好的可视化图形界面。     

Multisensor fusion-based gas detection module

This article develops a gas detection module for the intelligent home. The module uses eight gas sensors to detect the environment of the home and building. The gas sensors of the module have an NH₃ sensor, an air pollution sensor, an alcohol sensor, an HS sensor, a smoke sensor, a CO sensor, an LPG sensor, and a natural gas sensor, and can classify more than eight types of gas using multisensor fusion algorithms. In the logical filter method, either AND or OR filters can be implemented in the gas detection module. Then we can calculate the system’s reliability using the AND and OR filters, and classify the type of gas in the environment. The controller of the gas detection module is a HOLTEK microchip. The module can communicate with the supervised computer via a wire interface or a wireless RF interface, and can caution the user via a voice module. Finally, we present some experimental results to measure unknown gases using the gas detection module on the security system of an intelligent building and home.     

Multisensor based security robot system for intelligent building

Intelligent building can provide safety, convenience, efficiency and entertainment for life in the 21st century. The most importance role of the intelligent building is the security system. We develop a multi sensor-based intelligent security robot (ISR) that is widely employed in intelligent buildings. The intelligent security robot can detect abnormal and dangerous situations and notify users. The robot has the shape of cylinder and its diameter, height, and weight are 50 cm, 130 cm and 100 kg respectively. The function of the ISR contains six parts. There is the software development system; avoiding obstacle and motion planning system, image system, sensor system, remote supervise system and other systems. We develop a multi sensor-based sensor system in the ISR. We use multiple multisensor fusion algorithms to get an exact decision in the detection subsystem of the sensor system. There is an adaptive fusion method, a rule based method, and a statistical signal method. We demonstrate the remote supervisory system to control the ISR using a direct control mode and a behavior control mode. We think that the man–machine interface in a security robot system must have mobility and convenience. Therefore, we use a touch screen to display the system state, and design a general user interface (GUI) to service the user and visitors. The user can remotely control the appliance using a cell phone through a GSM modem, too. The appliance module can feedback reaction results to the user through a cell phone. Finally, we implement the fire detection system in the intelligent security robot (Chung-Cheng-I). If a fire occurs, the intelligent security robot can find out the fire source using the fire detection system. In intruder detection, we program the same scenario to detect the intruder using the intelligent security robot. The intelligent security robot transmits the message of the detection result to the user using a GSM modem for a fire event or intruder, and transmits the detection result to a client computer through the internet.     

智慧居家养老安防系统的设计与实现

系统从空巢老人的安全出发,融合互联网、物联网及无线传感器技术,完成智慧居家养老安防系统的设计实现,对老人的居住环境进行优化.从功能的角度出发,将系统分为软件和硬件模块设计.整体采用分治策略,对通信协议、单片机、外围传感器和语音模块进行设计,并将各个模块系统地结合起来,最终设计出成体系的智能家居养老安防系统.系统的实现主...     

Motion planning for a landmine-detection robot

This article describes a landmine-detection system that contains a landmine-detection mobile robot and a following mobile robot. In this system, the landmine-detection robot goes ahead, and uses a landmine detector and a GPS module to find a landmine, records the coordinates of its location, and transmits these coordinates to the following mobile robot via a wireless RF interface. The following robot can record the location and orientation of the landmine-detection robot and all the landmines in the region. The following robot moves close to the landmine, and programs a path to avoid obstacles and landmines automatically. The driving system of the landmine-detection mobile robot uses a microprocessor dsPIC 30F4011 as the core, and controls two DC servomotors to program the motion path. The user interface of the landmine-detection robot and the following robot uses Borland C₊₊ Builder language to receive the location data. In the experimental results, the landmine-detection robot records the location of landmines using a GPS module, and transmits the locations to the following robot via a wireless RF interface. The following robot avoids the landmines, and improves the safety of people or materials being carried through the landmine area.     

可无线编程的嵌入式小型机器人系统的实现

介绍的系统包括两大模块:以M16C/62微控制器为核心的机器人小车终端和PC机通过串口与无线模块连接组成的主控端,在此系统的基础上重点讨论了无线数据传输协议的设计、无线编程及无线下载程序的实现.     

Man-machine interface for modular robot systems

A modular robot is composed of multiple modules, each comprising a sensor, an actuator, and a control system. Each module accumulates information about its own sensor, actuator, and connections to other modules, as well as communication information between adjoining modules. The user obtains this information via an interface, and can thus recognize the state of the robot and issue commands. However, when the number of modules becomes large, the amount of information sent from the modules becomes too much for the user to deal with effectively. Naturally, it also becomes more difficult for the user to issue commands to the modular robot as the number of modules increases. In this study, we developed an interface to present, in a simple manner, information aggregated in a certain module from other modules, and we examined its effectiveness in a modular robot composed of these modules.     

面向智能家居平台的信息物理融合系统安全

作为物联网技术的典型应用,智能家居平台正逐步走进千家万户,但其存在的安全问题阻碍了其进一步的部署.研究者对智能家居平台的安全问题研究处于起步阶段,同时大量安全威胁被迅速提出.回顾了当前智能家居平台的典型架构,并分析了其各个组成部分存在的攻击接口.在信息接口安全方面,分析了存在于如智能摄像头的图像接口与语音控制系统的对抗样本攻击问题;在云端后台安全方面,分析了执行云端智能应用时对安全规则的破坏,以及造成的隐私泄露等问题.回顾了对这些安全问题所提出的解决方案,并指出现有工作存在的问题.针对存在于智能家居中的恶意应用问题,提出了一种基于无线流量分析的第三方恶意软件检测系统,能够在不修改智能家居平台的情况下,实现对恶意应用的精准检测.介绍了该系统的相关设计方案,并在三星SmartThings平台上验证了其准确性,并针对该系统给出一个隐私保护机制.     

面向多网关的无线传感器网络多因素认证协议

无线传感器网络作为物联网的重要组成部分,广泛应用于环境监测、医疗健康、智能家居等领域.身份认证为用户安全地访问传感器节点中的实时数据提供了基本安全保障,是保障无线传感器网络安全的第一道防线;前向安全性属于系统安全的最后一道防线,能够极大程度地降低系统被攻破后的损失,因此一直被学术及工业界视为重要的安全属性.设计面向多网关的可实现前向安全性的无线传感器网络多因素身份认证协议是近年来安全协议领域的研究热点.由于多网关无线传感器网络身份认证协议往往应用于高安全需求场景,一方面需要面临强大的攻击者,另一方面传感器节点的计算和存储资源却十分有限,这给如何设计一个安全的多网关无线传感器网络身份认证协议带来了挑战.近年来,大量的多网关身份认证协议被提出,但大部分都随后被指出存在各种安全问题.2018年,Ali等人提出了一个适用于农业监测的多因素认证协议,该协议通过一个可信的中心(基站)来实现用户与外部的传感器节点的认证;Srinivas等人提出了一个通用的面向多网关的多因素身份认证协议,该协议不需要一个可信的中心,而是通过在网关之间存储共享秘密参数来完成用户与外部传感器节点的认证.这两个协议是多网关无线传感器网络身份认证协议的典型代表,分别代表了两类实现不同网关间认证的方式:1)基于可信基站,2)基于共享秘密参数.分析指出这两个协议对离线字典猜测攻击、内部攻击是脆弱的,且无法实现匿名性和前向安全性.鉴于此,本文提出一个安全增强的可实现前向安全性的面向多网关的无线传感器网络多因素认证协议.该协议采用Srinivas等协议的认证方式,即通过网关之间的共享秘密参数完成用户与外部传感器节点的认证,包含两种典型的认证场景.对新协议进行了BAN逻辑分析及启发式分析,分析结果表明该协议实现了双向认证,且能够安全地协商会话密钥以及抵抗各类已知的攻击.与相关协议的对比结果显示,新协议在提高安全性的同时,保持了较高的效率,适于资源受限的无线传感器网络环境.     

Robust one-time password authentication scheme using smart card for home network environment

Due to the exponential growth of the Internet users and wireless devices, interests on home networks have been enormously increased in recent days. In digital home networks, home services including remote access and control to home appliances as well as services offered by service providers are alluring. However, the remote control services cause digital home networks to have various security threats. Hence, for digital home networks, robust security services, especially remote user authentication, should be considered. This paper presents a robust and efficient authentication scheme based on strong-password approach to provide secure remote access in digital home network environments. The proposed scheme uses lightweight computation modules including hashed one-time password and hash-chaining technique along with low-cost smart card technology. It aims to satisfy several security requirements including stolen smart card attack and forward secrecy with lost smart card as well as functional requirements including no verification table and no time synchronization. Comparing with the existing representative schemes, it can be validated that the proposed scheme is more robust authentication mechanism having better security properties. We have conducted formal verification of the proposed scheme.     

基于RF的智能家居无线通信网络系统设计

将基于433MHz频段的无线RF模块应用于智能家居系统中,用于组建家庭内部无线通信网络系统。其低成本、低功耗、穿越障碍能力强和体积小等特点,非常适合在智能家居系统中普及应用。最终使普通人群能够体验物联网智能家居生活。