Hanita Daud

Smart parking reservation system using short message services (SMS)

This paper proposes a smart parking system to solve the problem of unnecessary time consumption in finding parking spot in commercial car park areas. A parking reservation system is developed in such a way that users book their parking spots through short message services (SMS). The SMS sent will be processed by a wireless communication instrumentation device called micro-RTU (Remote Terminal Unit). This micro-RTU will reply the confirmation of booking by giving the details of reservation like password and lot number. The password will be used to enter the parking area and valid for a certain period of time. The system is fully automated with the use of the Peripheral Interface Controller (PIC). This microcontroller is capable in storing information of empty parking spaces, provide passwords as well as allowing or denying access to the parking area. A prototype of a car park system has been designed to demonstrate the capability of the proposed work. The demonstration has proven the capability of the system to reserve the parking, gain entry to the parking area and hence eliminates the hassle of searching empty parking lots.

WI-FI ENERGY HARVESTER FOR LOW POWER RFID APPLICATION

In recent years, active Radio Frequency Identiflcation (RFID) tags have crossed into ultra low power domain. With obvious advantages over passive tags, a setback for active tag growth is the need for battery replacement and limited operational life. Battery life could be extended by scavenging surrounding Wi-Fi signals using rectenna architecture which consists of a receiving antenna attached to a rectifying circuit. A seven stage Cockroft-Walton voltage multiplier optimized for low input power (below 0dBm) is proposed. Prototype was fabricated on RT/Duroid 5880 (RO5880) printed circuit board (PCB) substrate with dielectric constant and loss tangent of 2.2 and 0.0009 respectively. Experimental results show that 2V output voltage can be harvested from an operating frequency of 2.48GHz with i9dBm (0.13mW) sensitivity with 1.57mm board thickness.

Rectenna architecture based energy harvester for low power RFID application

Large scale implementation of active RFID tag technology has been restricted by the need for battery replacement. Prolonging battery lifespan may potentially promote active RFID tags which offer obvious advantages over passive RFID systems. This paper explores some opportunities to simulate and develop a prototype RF energy harvester for 2.4 GHz band specifically designed for low power active RFID tag application. This system employs a rectenna architecture which is a receiving antenna attached to a rectifying circuit that efficiently converts RF energy to DC current. Initial ADS simulation results show that 2 V output voltage can be achieved using a 7 stage Cockroft-Walton rectifying circuitry with -4.881 dBm (0.325 mW) output power under -4 dBm (0.398 mW) input RF signal. These results lend support to the idea that RF energy harvesting is indeed promising.

Application of ZnO Nanoparticles EM Wave Detector Prepared by Sol- gel and Self-Combustion Techniques

Zinc oxide (ZnO) has found many important applications such as optoelectronic devices, sensors and varistors. The challenging part however is synthesizing ZnO nanoparticles and its utilisation as EM detectors. Sol-gel and self-combustion techniques were chosen in this study due to the ability to produce single phase and nano-size samples. The starting mixture consists of 10 grams of zinc (II) nitrate, Zn(NO3)2.6H2O salt which was dissolved in 50 mL of nitric acid, HNO3.The solution was stirred at 250 rpm continuously for 1 day. The mixture was then gradually heated for every 15 minutes until it combusted at 110oC for the self-combustion technique. For the sol-gel technique, the dissolved mixture was heated at 40oC, 50oC, 60oC and 70oC until the gelatine was formed. After the drying process, the as-prepared samples were annealed at 100oC and 200 oC for 1 hour for each technique. Characterizations were performed by using X-Ray Diffraction (XRD), Raman Spectra and Scanning Electron Microscopy (SEM).The XRD analysis showed a major peak of [101] plane at 2Ө for the self-combustion technique and the sol-gel technique. Raman results for the samples prepared via sol-gel and self-combustion techniques had shown the major peak of ZnO that is located at the Raman shifts of 437.67 cm-1. Using the Scherrer equation, single crystal nano particle of ZnO was successfully obtained in the range of 38.49 nm to 50.70 nm for the sample prepared via the sol gel technique. By the self-combustion technique, the average dimension of the as-prepared sample is in the range of 34-49 nm. Further heat treatment resulted in a major change of the Raman shift corresponding to the single phase ZnO nano particles. The best samples were used as electromagnetic (EM) detectors. The EM detectors are polymer based composite which were prepared using a casting technique.

Air waves effect on sea bed logging for shallow water application

Sea bed logging (SBL) is a technique for finding resistive layers, which can be hydrocarbon reservoirs in the subsurface using marine controlled source electromagnetic (CSEM) survey. In CSEM, a mobile horizontal electric dipole (HED) source transmits low frequency EM signal which is towed over an array of seafloor receivers measuring the electric and/or magnetic field. This EM signal induces an airwave along the air/sea surface that interferes with the signal that comes from the subsurface and this airwave will start dominating at larger offsets. Airwave is actually the energy that propagates from the source through the atmosphere to the receiver on the seabed. Airwave component is problematic in shallow water because it is less attenuated during its up and down propagation compared to deeper water. This paper will present the air wave amplitude verses water depth relationship. Using the simulator that has been developed using MATLAB software we will set up a forward model that contains air, sea water, sediments and hydrocarbon reservoir with their resistivity values respectively. Sea water depth will be varied starting from 250m and is incremented every 250m until the airwaves signal captured by the receiver becomes insignificant or approaching to zero. From this simulation we shall find the water depth on which airwave has less effect on the desired forward model.

Monitoring Heart Rate and Body Temperature Using Wireless Technology (Zigbee)

Wireless technology has increasingly emerged as one of the demanding technologies in healthcare industry. Monitoring patients’ condition is a crucial task in any hospital to ensure patients are in good and stable condition. Wireless sensor network is the solution and has been widely introduced in measuring vital signs of patients such as temperature, heart rate, oxygen saturation, respiratory rate and others from remote location. Zigbee Network or accurately known as IEEE 802.15.4/Zigbee on the other hand is known to be a low power consumption device with good and stable data transmission range, higher network flexibility and large number of nodes. This work is discussing on integrating heart rate and temperature sensors to a wireless transceiver Zigbee (Xbee) module and is used to measure patients’ conditions from remote location (nurse’s station). Series of tests have been conducted using these devices to measure patients’ heart rate and body temperature for different genders and age group at lying down position. This is to ensure that the devices developed are reliable, stable and producing the same results as conventional devices (thermometer and heart beat reader). Results obtained are very encouraging; the developed devices are producing stable readings and are capable of transmitting information at reasonable distance.

Powering LED from Wi-Fi: A qualitative assessment for rectenna design

With vast benefits across various market segments, active RFID tags have shown great potential in the healthcare sector. Battery replacement remains a deterrent towards mass implementation of active RFID tag technology. Within this context, rectenna architecture has been investigated as the RF power transfer mechanism for ultra low power on-body communication. A working prototype consisting of 7-stage Cockroft-Walton voltage multiplier integrated with band pass filter and lowpass filter has successfully been developed on 1.57 mm RT/Duroid 5880 laminate with the goal of prolonging battery lifespan. A qualitative assessment is proposed as means of evaluating rectenna performance with various antenna designs connected to optimized rectifier. Under non-controlled environment, powering an LED from a Wireless Access Point transmitter source can be used to gauge robustness of rectenna system. Antenna with 5 dBi gain was capable of powering LED at 10 cm distance from RF source.

Investigation of Stability and Reliability of the Patient's Wireless Temperature Monitoring Device

Abstract Currently, wireless radio frequency (RF) communication and Wireless Sensor Network (WSN) has shifted its trend on human or item tracking capability to real time monitoring capability especially in healthcare industry. Monitoring patients condition is one of the crucial tasks in any hospital to ensure patients are in good and stable condition. Efforts have been made by many researchers to use WSN to measure temperature, heart rate, oxygen saturation, respiratory rate and etc. to monitor patients condition remotely in hospitals. This research focuses on integrating a temperature sensor to a wireless transceiver Zigbee network and is used to measure patients body temperature from remote location (nurses workstation. Few thermistor temperature sensors were used to determine reliability and their reading were compared against thermometer and the one with an accurate and stable reading was chosen. Zigbee network or accurately known as IEEE 802.15.4/Zigbee is known to be a low power consumption device with better transmission range, higher network flexibility and large number of nodes. Through the experimentation, Zigbee network is proven capable to provide stability in data transmission at longer range at different temperature environment.

Effect of Frequency on Hydrocarbon (HC) Detection Using 3D Finite Integral Modeling

Detection of hydrocarbon in sea bed logging (SBL) is still a very challenging task for deep target reservoirs. The response of electromagnetic (EM) field from marine environment is very low and it is very difficult to predict deep target reservoirs below 2500 m from the sea floor. Straight antennas at 0.125 Hz and 0.0625 Hz are used for the detection of deep target hydrocarbon reservoirs below the seafloor. The finite integration method (FIM) is applied on 3D geological seabed models. The proposed area of the seabed model (16 km ×16 km) was simulated by using CST (computer simulation technology) EM studio. The comparison of different frequencies for different target depths was done in our proposed model. Total electric and magnetic fields were applied instead of scattered electric and magnetic fields, due to its accurate and precise measurements of resistivity contrast at the target depth up to 3000 m. From the results, it was observed that straight antenna at 0.0625 Hz shows 50.11% resistivity contrast at target depth of 1000 m whereas straight antenna at 0.125 Hz showed 42.30% resistivity contrast at the same target depth for the E-field. It was found that the E-field response decreased as the target depth increased gradually by 500 m from 1000 m to 3000 m at different values of frequencies with constant current (1250 A). It was also investigated that at frequency of 0.0625 Hz, straight antenna gave 7.10% better delineation of hydrocarbon at 3000 m target depth. It was speculated that an antenna at 0.0625 Hz may be able to detect hydrocarbon reservoirs at 4000 m target depth below the seafloor. This EM antenna may open a new frontier for oil and gas industry for the detection of deep target hydrocarbon reservoirs below the seafloor.

Detecting space-time disease clusters with arbitrary shapes and sizes using a co-clustering approach

Ability to detect potential space-time clusters in spatio-temporal data on disease occurrences is necessary for conducting surveillance and implementing disease prevention policies. Most existing techniques use geometrically shaped (circular, elliptical or square) scanning windows to discover disease clusters. In certain situations, where the disease occurrences tend to cluster in very irregularly shaped areas, these algorithms are not feasible in practise for the detection of space-time clusters. To address this problem, a new algorithm is proposed, which uses a co-clustering strategy to detect prospective and retrospective space-time disease clusters with no restriction on shape and size. The proposed method detects space-time disease clusters by tracking the changes in space-time occurrence structure instead of an in-depth search over space. This method was utilised to detect potential clusters in the annual and monthly malaria data in Khyber Pakhtunkhwa Province, Pakistan from 2012 to 2016 visualising the results on a heat map. The results of the annual data analysis showed that the most likely hotspot emerged in three sub-regions in the years 2013-2014. The most likely hotspots in monthly data appeared in the month of July to October in each year and showed a strong periodic trend.