Design of Spy Robot with Wireless Night Vision Camera Using Android

The main objective behind this Project is to develop a robot to perform the act of surveillance human activities using wireless night vision camera and Robots can be manually controlled using IOT android application. The robot consists of night vision wireless camera which can transmit videos of the human. The purpose of this robot is to roam around and provide audio and video information from the given environment and to send that obtained information to the user with metal detection. In this project, one can control the robot with the help of mobile. This robot will collect data from remote place and able to send those data to a remote IoT cloud database. We can control the movement of the robot by sending instructions via IOT app from our android phone. a multipurpose Robotic vehicle moves Forward, Left, Right, Backward and Stop directions which can be constrained by ESP32 In proposed system we are going to designed a low-cost Microcontroller Based Android controlled Robot. The robot will move forward, backward, left and right direction by following the instructions given from the mobile. This system can be helpful for various purposes. Our project aims to provide a robotic vehicle equipped with a wireless camera having night vision capability for remote monitoring/spying purposes with metal detect alerts. The night vision camera allows for transmitting real time night vision video even in dark environments. Whatever is recorded by the camera can be viewed in PC for reference. Keywords: Robotic Surveillance, Wireless Night Vision Camera, IoT Control, Metal Detection, ESP32 Microcontroller

The rapid proliferation of wireless video cameras has raised serious privacy concerns. In this paper, we propose a stimulating-and-probing approach to detecting wireless spy cameras. The core idea is to actively alter the light condition of a private space to manipulate the spy camera's video scene, and then investigates the responsive variations of a packet flow to determine if it is produced by a wireless camera. Following this approach, we develop Blink and Flicker -- two practical systems for detecting wireless spy cameras. Blink is a lightweight app that can be deployed on off-the-shelf mobile devices. It asks the user to turn on/off the light of her private space, and then uses the light sensor and the wireless radio of the mobile device to identify the response of wireless cameras. Flicker is a robust and automated system that augments Blink to detect wireless cameras in both live and offline streaming modes. Flicker employs a cheap and portable circuit, which harnesses daily used LEDs to stimulate wireless cameras using human-invisible flickering. The time series of stimuli is further encoded using FEC to combat ambient light and uncontrollable packet flow variations that may degrade detection performance. Extensive experiments show that Blink and Flicker can accurately detect wireless cameras under a wide range of network and environmental conditions.

This paper addresses a real-time implementation of face recognition system with LEGO Mindstorms NXT robot and wireless camera. This system is organized to capture an image sequence, find the features of face in the images, and recognize and verify a person. Moreover, this system can collect the facial images of various poses due to movable robot, which enables this system to increase performance. The current implementation uses the LDA(Linear Discriminant Analysis) learning algorithm considering the number of training data. We have made several tests on video data, and measured the performance and the speed of the proposed system in real environment. Finally, the result has confirmed that the proposed system is better than conventional PC-based systems.KeywordsLEGO Mindstorms NXT robotreal-time face recognition

The paper proposes a transmission system for Motion-JPEG2000 video in mobile communications. In Motion JPEG2000, video data are compressed in frames according to JPEG2000 part1. In JPEG2000 part1 encoding, an input image is coded in the order of significant sub-bands, which are low-frequency bands. The proposed transmission system therefore assigns each sub-band data suitable weights according to their significance by using orthogonal multi-code CDMA so that bit errors are concentrated in the high-frequency sub-bands which are of little significance on image reconstruction. Concretely speaking, copies of significant sub-band data are made and the copied data are orthogonally multiplexed. The multiplexed data are averaged in the receiver so that the bit errors of significant sub-bands are reduced. On the other hand, the other sub-band data are not copied in order to increase transmission rates. Furthermore, audio data are transmitted with high quality by orthogonal multiplexing. The proposed system adaptively performs the above process for video and audio data. Moreover, these proposed systems are effective in the progressive order of LRCP (layer - resolution level - component - position) and of RLCP (resolution level - layer - component - position) on JPEG2000. Simulation results demonstrate that the proposed system can improve image quality compared with the conventional transmission system under the same BER.

There are some causes of car accidents due to driver error which includes drunkenness, fatigue and drowsiness. Hence, the system is needed which will alert driver before he/she falls asleep and number of accidents can be reduced. In the proposed system, a camera continuously captures movement of the driver. To determine whether a driver is feeling drowsy or not the head position, eye closing duration and eye blink rate are used. Using this information, the drowsiness level is determined. As per the drowsiness level the alarm is generated. A night vision camera is used to handle different light conditions.

Working under low light conditions is of particular interest in machine vision applications such as night vision, tone-mapping techniques, low-light imaging, photography, and surveillance cameras. This work aims at investigating the perception of color at low light situations imposed by physical principles governing photon emission. The impact of the probabilistic nature of photon emission on our color perception becomes more significant at low light levels. In this regard, physical principles are leveraged to develop a framework to take into account the effects of low light level on color vision. Results of this study shows that the normalized spectral power distribution of light changes with light intensity and becomes more uncertain at low light situation as a result of which the uncertainty of color perception increases. Furthermore, a color patch at low light levels give rise to uncertain color measurements whose chromaticities form an elliptic shape inside the chromaticity diagram around the high intensity chromaticity of the color patch. The size of these ellipses is a function of the light intensity and the chromaticity of color patches however the orientation of the ellipses depends only on the patch chromaticity and not on the light level. Moreover, the results of this work indicate that the spectral composition of light is a determining factor in the size and orientation of the ellipses. The elliptic shape of measured samples is a result of the Poisson distribution governing photon emission together with the form of human cone spectral sensitivity functions and can partly explain the elliptic shape of MacAdam ellipses.

With smartphones and other web-enabled mobile devices growing quickly in popularity, higher education institutions have the opportunity -- and challenge -- to leverage this young medium to provide dynamic content regarding services, events, and support documentation, among others. In late 2009, Lehigh University released an iPhone app dubbed LehighU Live. The mobile device market has changed significantly since then with the addition of the widely-popular Android operating system and others like Blackberry and Windows Phone 7. In spring 2011, the student technology support team revamped their web presence with the goal of also offering support services via students' mobile devices. Our first responsibility was to provide a mobile application that can be used across platforms; however, we also wanted the user experience to feel the same as any other app on a given platform. For example, our app should feel like an Android app if the student is using an Android phone. Our second responsibility was to ensure that we could deliver dynamic content to students quickly regarding services, updates, support tips, and real-time alerts. These two major responsibilities presented significant challenges, not the least of which is that we do not have the resources to develop and/or maintain a separate app for each platform while also managing and pushing out the types of content we needed to get to students quickly. Therefore, we began looking at cross-platform mobile development frameworks such as the Mobile Web Framework (MWF) released by UCLA and other device-agnostic approaches. The challenge quickly became to build a solid, web-based mobile application that could be delivered via an app for individual platforms while at the same time accessible and uasble via mobile web browser for other web-enabled mobile devices.

Recent advances in mobile technologies have enabled a plethora of new applications. The hardware capabilities of mobile devices, however, are still insufficient for real-time stream data processing (e.g., real-time video stream). In order to process real-time streaming data, most existing applications offload the data and computation to a remote cloud service, such as Apache Storm or Apache Spark Streaming. Offloading streaming data, however, has high costs for users, e.g., significant service fees and battery consumption. To address these challenges, we design, implement and evaluate Mobile Storm, the first stream processing platform for mobile clouds, leveraging clusters of local mobile devices to process real-time stream data. In Mobile Storm, we model the workflow of a real-time stream processing job and decompose it into several tasks so that the job can be executed concurrently and in a distributed manner on multiple mobile devices. Mobile Storm was implemented on Android phones and evaluated extensively through a real-time HD video processing application. The result shows that Mobile Storm effectively processes HD Video Stream in a mobile cloud, which would be impossible on a single mobile device.

This research is carried out for the development and implementation of an end-to-end encrypted Short Message Service (SMS) App, utilizing a hybrid cipher algorithm, driven by the notable insecurity observed in SMS communications on mobile devices. SMS is a widely used communication method, and the primary goal of this study is to create a system (App) for end-to-end encrypted SMS. Loss of phones is becoming vulnerable for threats, because we store vital records in android and these records are secret such that no other third party is required to see them, such as Bank SMS, Event Notification etc. Also this information can be compromised if android phone is been lost and found by the criminals. Kidnapping activity is serious case happening in northern part of Nigeria, so if a phone is being lost and discovered how financed he is (the device holder), there is any means of bank account compromisation as that would allow the bank to give some information about the account because of the registered SIM card inserted in android devices (phones). This system is aimed to secure Bank SMS by not allowing an unauthorized person to views the banks SMS, but all other SMS can be view. Whenever the Banks SMS is received by the Android phone, the system will encrypt it and can only be viewed if using correct decryption key, a notification will be sent to the owner other phone if more than two attempt to view the message is made, using a Hybrid Cipher...

In the paper the features of protocols and the basic methods of organization of multimedia information transfer in telecommunication networks and distributed corporate safety networks are represented. The analysis of formats of basic elements of signals used in standards of multimedia information transfer is given.

The rapid rise in the technology today has brought to limelight mobile devices which are now being used as a tool to commit crime. Therefore, proper steps need to be ensured for Confidentiality, Integrity, Authenticity and legal acquisition of any form of digital evidence from the mobile devices. This study evaluates some mobile forensic tools that were developed mainly for mobile devices memory and SIM cards. An experiment was designed with five android phones with different Operating System. Four tools were used to find out the capability and efficiency of the tools when used on the sampled phones. This would help the forensic investigator to know the type of tools that will be suitable for each phone to be investigated for acquiring digital evidence. The evaluation result showed that AccessData FTK imager and Paraben device seizure performs better than Encase and Mobiledit. The experimental result shows that, Encase could detect the unallocated space on the mobile deice but could retrieve an deleted data.

This paper describes the system design considerations of an ultra low power wireless camera (Figure 1). The function of this camera is to acquire, compress, code and transmit video data over a wireless link. The data rate is variable up to a maximum of 1Mbps (the image sensor has a spatial resolution of 256×256 quantized to 8 bits/pixel). Many of the design issues faced in the context of our wireless camera are common to those in other wireless applications. Total system power (computation as well as transmission) averaged over the normal operating conditions of the device should be minimized to maximize battery lifetime.

The applications of Augmented Reality (AR) in such mobile devices as phones and pads can enhance the users' experiences both in virtual and real world. In this paper the design and implementation of a Multiplayer Collaborative Training System (MCTS) is presented. It is a combination of virtual and physical reality, which builds virtual worlds with changeable scenes, brings authentic user experience and records process for analyzing and evaluation. Players are trained in a closed environment, which is composed of projectors, multimedia devices and physical scene. The application of mobile AR device guides the entire training process, and users make effective interaction with mobile devices to start and finish training mission. In the proposed system five innovative methods are implemented to improve interaction quality. An experiment case is devised with a series of tasks and conundrums for players, experimental results show that the MCTS can contribute more effective educations on team consciousness through the use of mobile AR technology and multimodal interaction to integrate virtual and real experience.

SummaryMobile devices are the primary communication tool in day to day life of the people. Nowadays, the enhancement of the mobile applications namely IoTApps and their exploitation in various domains like healthcare monitoring, home automation, smart farming, smart grid, and smart city are crucial. Though mobile devices are providing seamless user experience anywhere, anytime, and anyplace, their restricted resources such as limited battery capacity, constrained processor speed, inadequate storage, and memory are hindering the development of resource‐intensive mobile applications and internet of things (IoT)‐based mobile applications. To solve this resource constraint problem, a web service‐based IoT framework is proposed by exploiting fuzzy logic methodologies. This framework augments the resources of mobile devices by offloading the resource‐intensive subtasks from mobile devices to the service providing entities like Arduino, Raspberry PI controller, edge cloud, and distant cloud. Based on the recommended framework, an online Repository of Instructional Talk (RIoTalk) is successfully implemented to store and analyze the classroom lectures given by faculty in our study site. Simulation results show that there is a significant reduction in energy consumption, execution time, bandwidth utilization, and latency. The proposed research work significantly increases the resources of mobile devices by offloading the resource‐intensive subtasks from the mobile device to the service provider computing entities thereby providing Quality of Service (QoS) and Quality of Experience (QoE) to mobile users.

In this paper, a single speaker tracking mechanism with particle filter is presented for a reliable interaction with robot. To have a smooth tracking result, we use not only audio data but also video data. For sound observation, we use Time Delay Of Arrival (TDOA) between two microphones, and in order to expect high reliability in the likelihood of localization, we apply variable sensitivity values according to the angle of arrival for a triangle arrangement of microphones to calculate the likelihood for audio observation. For video observation, we use face detection routine of OpenCV which is widely available through the Internet. Together with audio and video data, we found out that more reliable source tracking is possible if we apply data fusion mechanism at every possible environment on a robot platform than single information.