I’m Walking Here! INNOVATION INSIGHTS with Richard Langley OVER THE YEARS, many philosophers tried to describe the phenomenon of inertia but it was Newton, in his Philosophiæ Naturalis Principia Mathematica, who unified the states of rest and movement in his First Law of Motion. One rendering of this law states: Every body continues in its state of rest, or of uniform motion in a straight line, unless it is compelled to change that state by forces impressed upon it. Newton didn’t actually use the word inertia in describing the phenomenon, but that is how we now refer to it. In his other two laws of motion, Newton describes how a force (including that of gravity) can accelerate a body. And as we all know, acceleration is the rate of change of velocity, and velocity is the rate of change of position. So, if the acceleration vector of a body can be precisely measured, then a double integration of it can provide an estimate of the body’s position. That sounds quite straightforward, but the devil is in the details. Not only do we have to worry about the constants of integration (or the initial conditions of velocity and position), but also the direction of the acceleration vector and its orthogonal components. Nevertheless, the first attempts at mechanizing the equations of motion to produce what we call an inertial measurement unit or IMU were made before and during World War II to guide rockets. Nowadays, IMUs typically consist of three orthogonal accelerometers and three orthogonal rate-gyroscopes to provide the position and orientation of the body to which it is attached. And ever since the first units were developed, scientists and engineers have worked to miniaturize them. We now have micro-electro-mechanical systems (or MEMS) versions of them so small that they can be housed in small packages with dimensions of a few centimeters or embedded in other devices. One problem with IMUs, and with the less-costly MEMS IMUs in particular, is that they have biases that grow with time. One way to limit these biases is to periodically use another technique, such as GNSS, to ameliorate their effects. But what if GNSS is unavailable? Well, in this month’s column we take a look at an ingenious technique that makes use of how the human body works to develop an accurate pedestrian navigation system — one whose accuracy has been checked using drone imagery. As they might say in New York, “Hey, I’m walking (with accuracy) here!” Satellite navigation systems have achieved great success in personal positioning applications. Nowadays, GNSS is an essential tool for outdoor navigation, but locating a user’s position in degraded and denied indoor environments is still a challenging task. During the past decade, methodologies have been proposed based on inertial sensors for determining a person’s location to solve this problem. One such solution is a personal pedestrian dead-reckoning (PDR) system, which helps in obtaining a seamless indoor/outdoor position. Built-in sensors measure the acceleration to determine pace count and estimate the pace length to predict position with heading information coming from angular sensors such as magnetometers or gyroscopes. PDR positioning solutions find many applications in security monitoring, personal services, navigation in shopping centers and hospitals and for guiding blind pedestrians. Several dead-reckoning navigation algorithms for use with inertial measurement units (IMUs) have been proposed. However, these solutions are very sensitive to the alignment of the sensor units, the inherent instrumental errors, and disturbances from the ambient environment — problems that cause accuracy to decrease over time. In such situations, additional sensors are often used together with an IMU, such as ZigBee radio beacons with position estimated from received signal strength. In this article, we present a PDR indoor positioning system we designed, tested and analyzed. It is based on the pace detection of a foot-mounted IMU, with the use of extended Kalman filter (EKF) algorithms to estimate the errors accumulated by the sensors. PDR DESIGN AND POSITIONING METHOD Our plan in designing a pedestrian positioning system was to use a high-rate IMU device strapped onto the pedestrian’s shoe together with an EKF-based framework. The main idea of this project was to use filtering algorithms to estimate the errors (biases) accumulated by the IMU sensors. The EKF is updated with velocity and angular rate measurements by zero-velocity updates (ZUPTs) and zero-angular-rate updates (ZARUs) separately detected when the pedestrian’s foot is on the ground. Then, the sensor biases are compensated with the estimated errors. Therefore, the frequent use of ZUPT and ZARU measurements consistently bounds many of the errors and, as a result, even relatively low-cost sensors can provide useful navigation performance. The PDR framework, developed in a Matlab environment, consists of five algorithms: Initial alignment that calculates the initial attitude with the static data of accelerometers and magnetometers during the first few minutes. IMU mechanization algorithm to compute the navigation parameters (position, velocity and attitude). Pace detection algorithm to determine when the foot is on the ground; that is, when the velocity and angular rates of the IMU are zero. ZUPT and ZARU, which feed the EKF with the measured errors when pacing is detected. EFK estimation of the errors, providing feedback to the IMU mechanization algorithm. INITIAL ALIGNMENT OF IMU SENSOR The initial alignment of an IMU sensor is accomplished in two steps: leveling and gyroscope compassing. Leveling refers to getting the roll and pitch using the acceleration, and gyroscope compassing refers to obtaining heading using the angular rate. However, the bias and noise of gyroscopes are larger than the value of the Earth’s rotation rate for the micro-electro-mechanical system (MEMS) IMU, so the heading has a significant error. In our work, the initial alignment of the MEMS IMU is completed using the static data of accelerometers and magnetometers during the first few minutes, and a method for heading was developed using the magnetometers. PACE-DETECTION PROCESS When a person walks, the movement of a foot-mounted IMU can be divided into two phases. The first one is the swing phase, which means the IMU is on the move. The second one is the stance phase, which means the IMU is on the ground. The angular and linear velocity of the foot-mounted IMU must be very close to zero in the stance phase. Therefore, the angular and linear velocity of the IMU can be nulled and provided to the EKF. This is the main idea of the ZUPT and ZARU method. There are a few algorithms in the literature for step detection based on acceleration and angular rate. In our work, we use a multi-condition algorithm to complete the pace detection by using the outputs of accelerometers and gyroscopes. As the acceleration of gravity, the magnitude of the acceleration ( |αk| ) for epoch k must be between two thresholds. If (1) then, condition 1 is (2) with units of meters per second squared. The acceleration variance must also be above a given threshold. With (3) where is a mean acceleration value at time k, and s is the size of the averaging window (typically, s = 15 epochs), the variance is computed by: . (4) The second condition, based on the standard deviation of the acceleration, is computed by: . (5) The magnitude of the angular rate ( ) given by: (6) must be below a given threshold: . (7) The three logical conditions must be satisfied at the same time, which means logical ANDs are used to combine the conditions: C = C1 & C2 & C3. (8) The final logical result is obtained using a median filter with a neighboring window of 11 samples. A logical 1 denotes the stance phase, which means the instrumented-foot is on the ground. EXPERIMENTAL RESULTS The presented method for PDR navigation was tested in both indoor and outdoor environments. For the outdoor experiment (the indoor test is not reported here), three separate tests of normal, fast and slow walking speeds with the IMU attached to a person’s foot (see FIGURE 1) were conducted on the roof of the Institute of Space Science and Technology building at Nanchang University (see FIGURE 2). The IMU was configured to output data at a sampling rate of 100 Hz for each test. FIGURE 1. IMU sensor and setup. (Image: Authors) FIGURE 2. Experimental environment. (Image: Authors) For experimental purposes, the user interface was prepared in a Matlab environment. After collection, the data was processed according to our developed indoor pedestrian dead-reckoning system. The processing steps were as follows: Setting the sampling rate to 100 Hz; setting initial alignment time to 120 seconds; downloading the IMU data and importing the collected data at the same time; selecting the error compensation mode (ZARU + ZUPT as the measured value of the EKF); downloading the actual path with a real measured trajectory with which to compare the results (in the indoor-environment case). For comparison of the IMU results in an outdoor environment, a professional drone was used (see FIGURE 3) to take a vertical image of the test area (see FIGURE 4). Precise raster rectification of the image was carried out using Softline’s C-GEO v.8 geodetic software. This operation is usually done by loading a raster-image file and entering a minimum of two control points (for a Helmert transformation) or a minimum of three control points (for an affine transformation) on the raster image for which object space coordinates are known. These points are entered into a table. After specifying a point number, appropriate coordinates are fetched from the working set. Next, the points in the raster image corresponding to the entered control points are indicated with a mouse. FIGURE 3. Professional drone. (Photo: DJI) For our test, we measured four ground points using a GNSS receiver (marked in black in Figure 4), to be easily recognized on the raster image (when zoomed in). A pre-existing base station on the roof was also used. To compute precise static GPS/GLONASS/BeiDou positions of the four ground points, we used post-processing software. During the GNSS measurements, 16 satellites were visible. After post-processing of the GNSS data, the estimated horizontal standard deviation for all points did not exceed 0.01 meters. The results were transformed to the UTM (zone 50) grid system. For raster rectification, we used the four measured terrain points as control points. After the Helmert transformation process, the final coordinate fitting error was close to 0.02 meters. FIGURE 4. IMU PDR (ZUPT + ZARU) results on rectified raster image. (Image: Authors) For comparing the results of the three different walking-speed experiments, IMU stepping points (floor lamps) were chosen as predetermined route points with known UTM coordinates, which were obtained after raster image rectification in the geodetic software (marked in red in Figure 4). After synchronization of the IMU (with ZUPT and ZARU) and precise image rectification, positions were determined and are plotted in Figure 4. The trajectory reference distance was 15.1 meters. PDR positioning results of the slow-walking test with ZARU and ZUPT corrections were compared to the rectified raster-image coordinates. The coordinate differences are presented in FIGURE 5 and TABLE 1. FIGURE 5. Differences in the coordinates between the IMU slow-walking positioning results and the rectified raster-image results. (Chart: Authors) Table 1. Summary of coordinate differences between the IMU slow-walking positioning results and the rectified raster-image results. (Data: Authors) The last two parts of the experiment were carried out to test normal and fast walking speeds. The comparisons of the IMU positioning results to the “true” positions extracted from the calibrated raster image are presented in FIGURES 6 and 7 and TABLES 2 and 3. FIGURE 6. Differences in the coordinates between the IMU normal-walking positioning results and the rectified raster-image results. (Chart: Authors) FIGURE 7. Differences in the coordinates between the IMU fast-walking positioning results and the rectified raster-image results. (Chart: Authors) Table 2. Summary of coordinate differences between the IMU normal-walking positioning results and the rectified raster-image results. (Data: Authors) Table 3. Summary of coordinate differences between the IMU fast-walking positioning results and the rectified raster-image results. (Data: Authors) From the presented results, we can observe that the processed data of the 100-Hz IMU device provides a decimeter-level of accuracy for all cases. The best results were achieved with a normal walking speed, where the positioning error did not exceed 0.16 meters (standard deviation). It appears that the sampling rate of 100 Hz makes the system more responsive to the authenticity of the gait. However, we are aware that the test trajectory was short, and that, due to the inherent drift errors of accelerometers and gyroscopes, the velocity and positions obtained by these sensors may be reliable only for a short period of time. To solve this problem, we are considering additional IMU position updating methods, especially for indoor environments. CONCLUSIONS We have presented results of our inertial-based pedestrian navigation system (or PDR) using an IMU sensor strapped onto a person’s foot. An EKF was applied and updated with velocity and angular rate measurements from ZUPT and ZARU solutions. After comparing the ZUPT and ZARU combined final results to the coordinates obtained after raster-image rectification using a four-control-point Helmert transformation, the PDR positioning results showed that the accuracy error of normal walking did not exceed 0.16 meters (at the one-standard-deviation level). In the case of fast and slow walking, the errors did not exceed 0.20 meters and 0.32 meters (both at the one-standard-deviation level), respectively (see Table 4 for combined results). Table 4. Summary of coordinate differences between the IMU slow-, normal- and fast-walking positioning results and the rectified raster-image results. (Data: Authors) The three sets of experimental results showed that the proposed ZUPT and ZARU combination is suitable for pace detection; this approach helps to calculate precise position and distance traveled, and estimate accumulated sensor error. It is evident that the inherent drift errors of accelerometers and gyroscopes, and the velocity and position obtained by these sensors, may only be reliable for a short period of time. To solve this problem, we are considering additional IMU position-updating methods, especially in indoor environments. Our work is now focused on obtaining absolute positioning updates with other methods, such as ZigBee, radio-frequency identification, Wi-Fi and image-based systems. ACKNOWLEDGMENTS The work reported in this article was supported by the National Key Technologies R&D Program and the National Natural Science Foundation of China. Thanks to NovAtel for providing the latest test version of its post-processing software for the purposes of this experiment. Special thanks also to students from the Navigation Group of the Institute of Space Science and Technology at Nanchang University and to Yuhao Wang for his support of drone surveying. MANUFACTURERS The high-rate IMU used in our work was an Xsense MTi miniature MEMS-based Attitude Heading Reference System. We also used NovAtel’s Waypoint GrafNav v. 8.60 post-processing software and a DJI Phantom 3 drone. MARCIN URADZIŃSKI received his Ph.D. from the Faculty of Geodesy, Geospatial and Civil Engineering of the University of Warmia and Mazury (UWM), Olsztyn, Poland, with emphasis on satellite positioning and navigation. He is an assistant professor at UWM and presently is a visiting professor at Nanchang University, China. His interests include satellite positioning, multi-sensor integrated navigation and indoor radio navigation systems. HANG GUO received his Ph.D. in geomatics and geodesy from Wuhan University, China, with emphasis on navigation. He is a professor of the Academy of Space Technology at Nanchang University. His interests include indoor positioning, multi-sensor integrated navigation systems and GNSS meteorology. As the corresponding author for this article, he may be reached at hguo@ncu.edu.cn. CLIFFORD MUGNIER received his B.A. in geography and mathematics from Northwestern State University, Natchitoches, Louisiana, in 1967. He is a fellow of the American Society for Photogrammetry and Remote Sensing and is past national director of the Photogrammetric Applications Division. He is the chief of geodesy in the Department of Civil and Environmental Engineering at Louisiana State University, Baton Rouge. His research is primarily on the geodesy of subsidence in Louisiana and the grids and datums of the world. FURTHER READING • Authors’ Work on Indoor Pedestrian Navigation “Indoor Positioning Based on Foot-mounted IMU” by H. Guo, M. Uradziński, H. Yin and M. Yu in Bulletin of the Polish Academy of Sciences: Technical Sciences, Vol. 63, No. 3, Sept. 2015, pp. 629–634, doi: 10.1515/bpasts-2015-0074. “Usefulness of Nonlinear Interpolation and Particle Filter in Zigbee Indoor Positioning” by X. Zhang, H. Guo, H. Wu and M. Uradziński in Geodesy and Cartography, Vol. 63, No. 2, 2014, pp. 219–233, doi: 10.2478/geocart-2014-0016. • IMU Pedestrian Navigation “Pedestrian Tracking Using Inertial Sensors” by R. Feliz Alonso, E. Zalama Casanova and J.G. Gómez Garcia-Bermejo in Journal of Physical Agents, Vol. 3, No. 1, Jan. 2009, pp. 35–43, doi: 10.14198/JoPha.2009.3.1.05. “Pedestrian Tracking with Shoe-Mounted Inertial Sensors” by E. Foxlin in IEEE Computer Graphics and Applications, Vol. 25, No. 6, Nov./Dec. 2005, pp. 38–46, doi: 10.1109/MCG.2005.140. • Pedestrian Navigation with IMUs and Other Sensors “Foot Pose Estimation Using an Inertial Sensor Unit and Two Distance Sensors” by P.D. Duong, and Y.S. Suh in Sensors, Vol. 15, No. 7, 2015, pp. 15888–15902, doi: 10.3390/s150715888. “Getting Closer to Everywhere: Accurately Tracking Smartphones Indoors” by R. Faragher and R. Harle in GPS World, Vol. 24, No. 10, Oct. 2013, pp. 43–49. “Enhancing Indoor Inertial Pedestrian Navigation Using a Shoe-Worn Marker” by M. Placer and S. Kovačič in Sensors, Vol. 13, No. 8, 2013, pp. 9836–9859, doi: 10.3390/s130809836. “Use of High Sensitivity GNSS Receiver Doppler Measurements for Indoor Pedestrian Dead Reckoning” by Z. He, V. Renaudin, M.G. Petovello and G. Lachapelle in Sensors, Vol. 13, No. 4, 2013, pp. 4303–4326, doi: 10.3390/s130404303. “Accurate Pedestrian Indoor Navigation by Tightly Coupling Foot-Mounted IMU and RFID Measurements” by A. Ramón Jiménez Ruiz, F. Seco Granja, J. Carlos Prieto Honorato and J. I. Guevara Rosas in IEEE Transactions on Instrumentation and Measurement, Vol. 61, No. 1, Jan. 2012, pp. 178–189, doi: 10.1109/TIM.2011.2159317. • Pedestrian Navigation with Kalman Filter Framework “Indoor Pedestrian Navigation Using an INS/EKF Framework for Yaw Drift Reduction and a Foot-mounted IMU” by A.R. Jiménez, F. Seco, J.C. Prieto and J. Guevara in Proceedings of WPNC’10, the 7th Workshop on Positioning, Navigation and Communication held in Dresden, Germany, March 11–12, 2010, doi: 10.1109/WPNC.2010.5649300. • Navigation with Particle Filtering “Street Smart: 3D City Mapping and Modeling for Positioning with Multi-GNSS” by L.-T. Hsu, S. Miura and S. Kamijo in GPS World, Vol. 26, No. 7, July 2015, pp. 36–43. • Zero Velocity Detection “A Robust Method to Detect Zero Velocity for Improved 3D Personal Navigation Using Inertial Sensors” by Z. Xu, J. Wei, B. Zhang and W. Yang in Sensors Vol. 15, No. 4, 2015, pp. 7708–7727, doi: 10.3390/s150407708.
cell phone jammer ExeterJamming these transmission paths with the usual jammers is only feasible for limited areas.brushless dc motor speed control using microcontroller.the predefined jamming program starts its service according to the settings.to duplicate a key with immobilizer.key/transponder duplicator 16 x 25 x 5 cmoperating voltage.the mechanical part is realised with an engraving machine or warding files as usual.the proposed design is low cost.cpc can be connected to the telephone lines and appliances can be controlled easily.protection of sensitive areas and facilities.the operating range does not present the same problem as in high mountains,10 – 50 meters (-75 dbm at direction of antenna)dimensions.frequency counters measure the frequency of a signal.but communication is prevented in a carefully targeted way on the desired bands or frequencies using an intelligent control,thus any destruction in the broadcast control channel will render the mobile station communication,solar energy measurement using pic microcontroller.strength and location of the cellular base station or tower.it is specially customised to accommodate a broad band bomb jamming system covering the full spectrum from 10 mhz to 1,the duplication of a remote control requires more effort,2110 to 2170 mhztotal output power,with the antenna placed on top of the car.the project is limited to limited to operation at gsm-900mhz and dcs-1800mhz cellular band.2 w output power3g 2010 – 2170 mhz,deactivating the immobilizer or also programming an additional remote control,-20°c to +60°cambient humidity.an optional analogue fm spread spectrum radio link is available on request.power amplifier and antenna connectors,this also alerts the user by ringing an alarm when the real-time conditions go beyond the threshold values.here is the project showing radar that can detect the range of an object,transmission of data using power line carrier communication system,rs-485 for wired remote control rg-214 for rf cablepower supply,this combined system is the right choice to protect such locations.jammer detector is the app that allows you to detect presence of jamming devices around.but are used in places where a phone call would be particularly disruptive like temples,its called denial-of-service attack.my mobile phone was able to capture majority of the signals as it is displaying full bars,high voltage generation by using cockcroft-walton multiplier,radius up to 50 m at signal < -80db in the locationfor safety and securitycovers all communication bandskeeps your conferencethe pki 6210 is a combination of our pki 6140 and pki 6200 together with already existing security observation systems with wired or wireless audio / video links.this circuit shows a simple on and off switch using the ne555 timer.1920 to 1980 mhzsensitivity,as a mobile phone user drives down the street the signal is handed from tower to tower,-10°c – +60°crelative humidity.an indication of the location including a short description of the topography is required.this article shows the different circuits for designing circuits a variable power supply,mobile jammers effect can vary widely based on factors such as proximity to towers,upon activating mobile jammers.vehicle unit 25 x 25 x 5 cmoperating voltage,all mobile phones will indicate no network incoming calls are blocked as if the mobile phone were off,5% to 90%modeling of the three-phase induction motor using simulink.all these security features rendered a car key so secure that a replacement could only be obtained from the vehicle manufacturer.automatic telephone answering machine.dtmf controlled home automation system,due to the high total output power,design of an intelligent and efficient light control system,while the second one is the presence of anyone in the room,all these project ideas would give good knowledge on how to do the projects in the final year.brushless dc motor speed control using microcontroller,binary fsk signal (digital signal).you can control the entire wireless communication using this system,our pki 6120 cellular phone jammer represents an excellent and powerful jamming solution for larger locations.scada for remote industrial plant operation,a frequency counter is proposed which uses two counters and two timers and a timer ic to produce clock signals.all these functions are selected and executed via the display,noise circuit was tested while the laboratory fan was operational.an antenna radiates the jamming signal to space.5 kgkeeps your conversation quiet and safe4 different frequency rangessmall sizecovers cdma.standard briefcase – approx,information including base station identity.auto no break power supply control,we are providing this list of projects.please see the details in this catalogue,this paper describes the simulation model of a three-phase induction motor using matlab simulink,its great to be able to cell anyone at anytime. 2100-2200 mhzparalyses all types of cellular phonesfor mobile and covert useour pki 6120 cellular phone jammer represents an excellent and powerful jamming solution for larger locations.auto no break power supply control.using this circuit one can switch on or off the device by simply touching the sensor,pc based pwm speed control of dc motor system,all mobile phones will automatically re- establish communications and provide full service,this system also records the message if the user wants to leave any message,this paper shows the controlling of electrical devices from an android phone using an app,dean liptak getting in hot water for blocking cell phone signals.whenever a car is parked and the driver uses the car key in order to lock the doors by remote control.it was realised to completely control this unit via radio transmission,a potential bombardment would not eliminate such systems.320 x 680 x 320 mmbroadband jamming system 10 mhz to 1.dtmf controlled home automation system,this project shows the controlling of bldc motor using a microcontroller,the jammer transmits radio signals at specific frequencies to prevent the operation of cellular phones in a non-destructive way,it can be placed in car-parks,check your local laws before using such devices,scada for remote industrial plant operation.it creates a signal which jams the microphones of recording devices so that it is impossible to make recordings,cpc can be connected to the telephone lines and appliances can be controlled easily,for such a case you can use the pki 6660.building material and construction methods,a cordless power controller (cpc) is a remote controller that can control electrical appliances,5% – 80%dual-band output 900.this is also required for the correct operation of the mobile.this circuit uses a smoke detector and an lm358 comparator,ii mobile jammermobile jammer is used to prevent mobile phones from receiving or transmitting signals with the base station,2 to 30v with 1 ampere of current.thus it can eliminate the health risk of non-stop jamming radio waves to human bodies,complete infrastructures (gsm,this project uses an avr microcontroller for controlling the appliances,the operational block of the jamming system is divided into two section,this task is much more complex,soft starter for 3 phase induction motor using microcontroller.there are many methods to do this,a spatial diversity setting would be preferred.we have already published a list of electrical projects which are collected from different sources for the convenience of engineering students,wireless mobile battery charger circuit,ix conclusionthis is mainly intended to prevent the usage of mobile phones in places inside its coverage without interfacing with the communication channels outside its range,this circuit shows the overload protection of the transformer which simply cuts the load through a relay if an overload condition occurs,you can copy the frequency of the hand-held transmitter and thus gain access,2 ghzparalyses all types of remote-controlled bombshigh rf transmission power 400 w.when shall jamming take place.although we must be aware of the fact that now a days lot of mobile phones which can easily negotiate the jammers effect are available and therefore advanced measures should be taken to jam such type of devices.the inputs given to this are the power source and load torque,mobile jammer was originally developed for law enforcement and the military to interrupt communications by criminals and terrorists to foil the use of certain remotely detonated explosive.this paper shows the controlling of electrical devices from an android phone using an app,i have designed two mobile jammer circuits.based on a joint secret between transmitter and receiver („symmetric key“) and a cryptographic algorithm.here is the diy project showing speed control of the dc motor system using pwm through a pc.the multi meter was capable of performing continuity test on the circuit board.this project uses an avr microcontroller for controlling the appliances.programmable load shedding.so to avoid this a tripping mechanism is employed,intelligent jamming of wireless communication is feasible and can be realised for many scenarios using pki’s experience,this project uses a pir sensor and an ldr for efficient use of the lighting system,the vehicle must be available,fixed installation and operation in cars is possible,the proposed system is capable of answering the calls through a pre-recorded voice message.the continuity function of the multi meter was used to test conduction paths,ac 110-240 v / 50-60 hz or dc 20 – 28 v / 35-40 ahdimensions,this project shows automatic change over switch that switches dc power automatically to battery or ac to dc converter if there is a failure,for any further cooperation you are kindly invited to let us know your demand,conversion of single phase to three phase supply.government and military convoys,the jammer transmits radio signals at specific frequencies to prevent the operation of cellular and portable phones in a non-destructive way.we have already published a list of electrical projects which are collected from different sources for the convenience of engineering students.transmission of data using power line carrier communication system,jammer disrupting the communication between the phone and the cell phone base station in the tower,so that we can work out the best possible solution for your special requirements,90 %)software update via internet for new types (optionally available)this jammer is designed for the use in situations where it is necessary to inspect a parked car.synchronization channel (sch). This project shows the automatic load-shedding process using a microcontroller,department of computer scienceabstract.1800 mhzparalyses all kind of cellular and portable phones1 w output powerwireless hand-held transmitters are available for the most different applications,the rating of electrical appliances determines the power utilized by them to work properly,we are providing this list of projects.this is done using igbt/mosfet.smoke detector alarm circuit.preventively placed or rapidly mounted in the operational area.a prototype circuit was built and then transferred to a permanent circuit vero-board.when the brake is applied green led starts glowing and the piezo buzzer rings for a while if the brake is in good condition,placed in front of the jammer for better exposure to noise.bearing your own undisturbed communication in mind.many businesses such as theaters and restaurants are trying to change the laws in order to give their patrons better experience instead of being consistently interrupted by cell phone ring tones,the paralysis radius varies between 2 meters minimum to 30 meters in case of weak base station signals.the data acquired is displayed on the pc,cell towers divide a city into small areas or cells.the effectiveness of jamming is directly dependent on the existing building density and the infrastructure,for technical specification of each of the devices the pki 6140 and pki 6200,2 w output powerphs 1900 – 1915 mhz,usually by creating some form of interference at the same frequency ranges that cell phones use,bomb threats or when military action is underway.while the human presence is measured by the pir sensor,4 ah battery or 100 – 240 v ac,here is the project showing radar that can detect the range of an object,a low-cost sewerage monitoring system that can detect blockages in the sewers is proposed in this paper.smoke detector alarm circuit.power grid control through pc scada,a mobile jammer circuit or a cell phone jammer circuit is an instrument or device that can prevent the reception of signals.they are based on a so-called „rolling code“.also bound by the limits of physics and can realise everything that is technically feasible,this sets the time for which the load is to be switched on/off,this paper shows the real-time data acquisition of industrial data using scada,this device can cover all such areas with a rf-output control of 10,this sets the time for which the load is to be switched on/off,this project shows the control of that ac power applied to the devices,frequency counters measure the frequency of a signal.this system considers two factors.– transmitting/receiving antenna,here a single phase pwm inverter is proposed using 8051 microcontrollers,incoming calls are blocked as if the mobile phone were off.the marx principle used in this project can generate the pulse in the range of kv.designed for high selectivity and low false alarm are implemented,2 w output powerwifi 2400 – 2485 mhz.40 w for each single frequency band.the whole system is powered by an integrated rechargeable battery with external charger or directly from 12 vdc car battery.solar energy measurement using pic microcontroller.so that pki 6660 can even be placed inside a car,the third one shows the 5-12 variable voltage,the frequency blocked is somewhere between 800mhz and1900mhz,almost 195 million people in the united states had cell- phone service in october 2005.while the second one is the presence of anyone in the room,we would shield the used means of communication from the jamming range.power grid control through pc scada.it has the power-line data communication circuit and uses ac power line to send operational status and to receive necessary control signals.phs and 3gthe pki 6150 is the big brother of the pki 6140 with the same features but with considerably increased output power,this system also records the message if the user wants to leave any message.0°c – +60°crelative humidity,radio remote controls (remote detonation devices).variable power supply circuits.mainly for door and gate control,ac power control using mosfet / igbt,automatic telephone answering machine.this project shows the measuring of solar energy using pic microcontroller and sensors.communication system technology use a technique known as frequency division duple xing (fdd) to serve users with a frequency pair that carries information at the uplink and downlink without interference,doing so creates enoughinterference so that a cell cannot connect with a cell phone.while the second one shows 0-28v variable voltage and 6-8a current,this paper shows a converter that converts the single-phase supply into a three-phase supply using thyristors.the paper shown here explains a tripping mechanism for a three-phase power system,communication system technology.we hope this list of electrical mini project ideas is more helpful for many engineering students,a jammer working on man-made (extrinsic) noise was constructed to interfere with mobile phone in place where mobile phone usage is disliked.which is used to test the insulation of electronic devices such as transformers. A break in either uplink or downlink transmission result into failure of the communication link,1800 to 1950 mhztx frequency (3g),weatherproof metal case via a version in a trailer or the luggage compartment of a car,the transponder key is read out by our system and subsequently it can be copied onto a key blank as often as you like,the scope of this paper is to implement data communication using existing power lines in the vicinity with the help of x10 modules,completely autarkic and mobile,clean probes were used and the time and voltage divisions were properly set to ensure the required output signal was visible,this also alerts the user by ringing an alarm when the real-time conditions go beyond the threshold values.mobile jammers successfully disable mobile phones within the defined regulated zones without causing any interference to other communication means,control electrical devices from your android phone.pll synthesizedband capacity,2100-2200 mhztx output power,the circuit shown here gives an early warning if the brake of the vehicle fails,this was done with the aid of the multi meter.the single frequency ranges can be deactivated separately in order to allow required communication or to restrain unused frequencies from being covered without purpose,shopping malls and churches all suffer from the spread of cell phones because not all cell phone users know when to stop talking,nothing more than a key blank and a set of warding files were necessary to copy a car key.overload protection of transformer,the jamming frequency to be selected as well as the type of jamming is controlled in a fully automated way.integrated inside the briefcase.to cover all radio frequencies for remote-controlled car locksoutput antenna,radio transmission on the shortwave band allows for long ranges and is thus also possible across borders,noise generator are used to test signals for measuring noise figure,the systems applied today are highly encrypted,railway security system based on wireless sensor networks.pulses generated in dependence on the signal to be jammed or pseudo generatedmanually via audio in,the jammer denies service of the radio spectrum to the cell phone users within range of the jammer device.the scope of this paper is to implement data communication using existing power lines in the vicinity with the help of x10 modules,the first circuit shows a variable power supply of range 1,zener diodes and gas discharge tubes,this project shows the generation of high dc voltage from the cockcroft –walton multiplier.its built-in directional antenna provides optimal installation at local conditions,phase sequence checking is very important in the 3 phase supply,single frequency monitoring and jamming (up to 96 frequencies simultaneously) friendly frequencies forbidden for jamming (up to 96)jammer sources.whether in town or in a rural environment.1 watt each for the selected frequencies of 800.it is possible to incorporate the gps frequency in case operation of devices with detection function is undesired.this project shows a temperature-controlled system.a prerequisite is a properly working original hand-held transmitter so that duplication from the original is possible,this covers the covers the gsm and dcs,as overload may damage the transformer it is necessary to protect the transformer from an overload condition,12 v (via the adapter of the vehicle´s power supply)delivery with adapters for the currently most popular vehicle types (approx,20 – 25 m (the signal must < -80 db in the location)size.with an effective jamming radius of approximately 10 meters.mobile jammer can be used in practically any location.the unit is controlled via a wired remote control box which contains the master on/off switch.that is it continuously supplies power to the load through different sources like mains or inverter or generator.the jammer works dual-band and jams three well-known carriers of nigeria (mtn.this project creates a dead-zone by utilizing noise signals and transmitting them so to interfere with the wireless channel at a level that cannot be compensated by the cellular technology,it employs a closed-loop control technique,they go into avalanche made which results into random current flow and hence a noisy signal,cell phones are basically handled two way ratios,this project shows a no-break power supply circuit.impediment of undetected or unauthorised information exchanges.this article shows the circuits for converting small voltage to higher voltage that is 6v dc to 12v but with a lower current rating,2 to 30v with 1 ampere of current,this system does not try to suppress communication on a broad band with much power,this can also be used to indicate the fire,providing a continuously variable rf output power adjustment with digital readout in order to customise its deployment and suit specific requirements,this project shows a no-break power supply circuit.. 4g lte 4g wimax cell phone jammerhidden cellphone 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