Health awareness is important with increasingly complex challenges towards maintaining good health, especially during the COVID-19 pandemic. Regular health monitoring is a must for everyone during the pandemic. This project proposed an IoT based E-Healthcare system to monitor the body temperature, blood pressure and heartbeat rate. The temperature sensor was connected to a Raspberry Pi microcontroller and the readings were stored in the SQLite database management system. The blood pressure and heartbeat rate readings were retrieved from the wrist blood pressure sensor and the readings were entered into the database. The user can access the health data record through a smartphone.
On most of the offshore oil and gas platforms, the current means of generating power are through the use of generators i.e. gas turbines and diesel power generators, or micro-generators for some smaller equipment. These generator sets are less reliable, especially on unmanned platforms. Hence, the deployment of renewable energy, such as the use of wind turbines, would be better for energy security, economic development and also protection of the environment. Instead of using wind power to power up the whole platform, small wind turbines can be utilised to power up some utilities and instrumentations on the platform, while having generators as back up, as the wind speed is beyond control. However, the capability of a small wind turbine in generating enough power is constantly under doubt as it is yet to be widely employed and only meagre data is available. This is caused by the issue of having insufficient studies regarding the implementation of small wind turbines for power generation on offshore oil and gas platforms. Hence, this paper studied the capability of small wind turbines for power generation on offshore platforms in Malaysia. Several models of small wind turbines were selected and their abilities in generating power to fulfil the annual energy consumption on a typical offshore platform were examined through precise calculations. The common offshore locations in Malaysia were identified and the average wind speeds from 2017 to 2019 at these locations were analysed. The result shows that certain models of small wind turbines are able to provide a significant amount of power for an offshore platform especially to power up the low power machineries. It was found that Kerteh, Terengganu is the most suitable offshore location to harness wind power due to its averagely high wind speed throughout the year. The highest amount of energy that can be produced was around 1445kWh per annum at Kerteh by the small wind turbine with the largest swept area and the lowest cut-in speed. This paper aims to serve as numerical validation on the plausibility of integrating small wind turbines for the generation of electricity on offshore platforms in Malaysia while also providing the recommended locations that are suitable for this region.
Memory modules are widely used in varies kind of electronics system design. The capacity of the memory modules has increased rapidly since the past few years in order to satisfy the high demand from the end-users. The memory modules’ manufacturers demand more units of automatic test equipment (ATE)to increase the production rate. However, the existing ATE used in the industry to carry out the memory testing is too costly(at least a million dollars per ATE tester). The low-cost memory testers are urgently needed to increase the production rate of the memory module. This has in spired us to design a low-cost memory tester. A low-cost memory fault detection tester with all the major fault detection algorithms that used in industry is modelled using Very High Speed Integrated Circuit Hardware Description Language (VHDL) in this paper to support the need of the low-cost ATE memory tester. The fault detection algorithms modelled are MATS+ (Modified Algorithm Test Sequence), MATS++, March C, March C-, March X ,March Y, zero-one and checkerboard scan tests. PERL program is used to analyse the simulation results and a log file will be generated at the end of the memory test. Extensive simulation and experimental test results show that the memory tester modelled covers all the memory test algorithms used in the industry. The low-cost memory fault detection tester designed provides the 100% fault detection coverage for all memory defects.
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