A nanogenerator (NG) is an energy harvester device that converts mechanical energy into electrical energy on a small scale by relying on physical changes. Piezoelectric semiconductor materials play a key role in producing high output power in piezoelectric nanogenerator. Low cost, reliability, deformation, and electrical and thermal properties are the main criteria for an excellent device. Typically, there are several main types of piezoelectric materials, zinc oxide (ZnO) nanorods, barium titanate (BaTiO₃) and lead zirconate titanate (PZT). Among those candidate, ZnO nanorods have shown high performance features due to their unique characteristics, such as having a wide-bandgap semiconductor energy of 3.3 eV and the ability to produce more ordered and uniform structures. In addition, ZnO nanorods have generated considerable output power, mainly due to their elastic nanostructure, mechanical stability and appropriate bandgap. Apart from that, doping the ZnO nanorods and adding doping impurities into the bulk ZnO nanorods are shown to have an influence on device performance. Based on findings, Ni-doped ZnO nanorods are found to have higher output power and surface area compared to other doped. This paper discusses several techniques for the synthesis growth of ZnO nanorods. Findings show that the hydrothermal method is the most commonly used technique due to its low cost and straightforward process. This paper reveals that the growth of ZnO nanorods using the hydrothermal method has achieved a high power density of 9 µWcm⁻².

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According to studies, up to 99 percent of alarms triggered in hospital units are false or clinically insignificant while indicating no genuine harm to patients. However, false alarms can lead to alert overload, causing healthcare workers to miss critical occurrences that could be harmful or even fatal. The purpose of this work is to tackle the problem by developing an integrated system that can continually track the patient's health condition utilising a cloud computing platform, allowing alerts to be targeted to the appropriate medical facility personnel in a timely and orderly manner. Arduino microcontrollers are used to collect health parameters such as temperature and pulse rate and provide a real-time monitoring system for medical practitioners. Multiple sensors and an RF transceiver are attached to a small microcontroller, forming a wearable module that the patient will wear. This wearable component is wirelessly connected to the main module consisting of a larger microcontroller, where the data is then uploaded to the database in the cloud through the internet. The data can then be accessed through a web-based terminal, providing medical practitioners access through the web page. If the system detects any abrupt changes to the patient's temperature or pulse rate, a push notification will be sent to the medical practitioner's Android smartphone so that immediate action can be taken. The system is scalable as multiple wearable modules can be connected to the main module, allowing monitoring of multiple patients simultaneously. More sensors can also easily be added to the wearable module to monitor other vital health parameters such as oxygen saturation and blood pressure. The testing has indicated that the system can achieve 99.4% accuracy in temperature monitoring and 86% accuracy for pulse monitoring.