Intelligent Home: Automated, Secured & Medically Monitored

This research focuses on Intelligent Home with security system, indoor and outdoor automation system and medical monitoring system with a mobile alert for retarded and impaired person. It presents the use of Android application to implement home security using RFID, dealing with outside home automation system using automated irrigation system techniques, inside home automation using smart sensors and medical remote monitoring system using implanted RFID tag. Voice commands and voice feedback and acknowledgment are also parts of the proposed system

An embedded implementation research initiative to tackle service delivery bottlenecks in the expanded programme on immunisation in Pakistan: Overview and reflections.

BACKGROUND: Embedded implementation research (IR) can play a critical role in health systems strengthening by tackling systems and implementation bottlenecks of a program. To achieve this aim, with the financial support of GAVI, the Vaccine Alliance, in 2016, the Government of Pakistan, UNICEF and the Alliance for Health Policy and Systems Research (AHPSR) launched an Embedded IR for Immunisation Initiative (the Initiative) to explore health systems and implementation bottlenecks, and potential strategies to tackle such bottlenecks in the Expanded Programme on Immunisation (EPI) in Pakistan. In total, 10 research teams were involved in the Initiative, which was the first of its kind in the country. In this paper, we provided a brief overview of the Initiative's approach as well as the key learnings including challenges and successes of the research teams which could inform future embedded IR Initiatives. METHODS: Data were collected from members of the IR teams through an online survey. In addition, in-depth interviews were conducted via phone and in-person from IR team members to explore further the challenges they faced while conducting IR in Pakistan and recommendations for future IR initiatives. The qualitative information obtained from these sources was collated and categorized into themes reflecting some of the challenges, successes, and lessons learned, as well as teams' recommendations for future initiatives. RESULTS: The embedded IR Initiative in Pakistan followed several steps starting with a desk review to compile information on key implementation challenges of EPI and ended with a dissemination workshop where all the research teams shared their IR results with policymakers and implementers. Key factors that facilitated the successful and timely completion of the studies included appreciation by and leadership of implementers in generation and use of local knowledge, identification of research priorities jointly by EPI managers and researchers and provision of continuous and high-quality support from in-country research partners. Participants in the Initiative indicated that challenges included a lack of clarity on the role and responsibilities of each partner involved and need for further support to facilitate use and dissemination of research findings. CONCLUSIONS: The Initiative established that an immunisation programme in a lower middle-income country can use small and time-bound embedded IR, based on partnerships between programme managers and local researchers, to generate information and evidence that can inform decision-making. Future embedded IR initiatives should strive to ensure effective coordination and active participation of all key stakeholders, a clear research utilisation plan from the outset, and efforts to strengthen research teams' capacity to foster utilisation of research findings

Distant temperature and humidity monitoring: prediction and measurement

Sensing environmental measuring parameters has a pivotal role in our everyday lives. Most of our daily life activities depend upon environmental conditions. Accurate information about these parameters also helps in several industrial applications like ventilation rate calculation, energy prediction, stock maintenance in warehouses, and saving from harmful conditions. The emergence of machine learning can make it easy to predict such time series problems. This paper describes the design of a remotely controlled robotic car for measuring and predicting humidity and temperature. A customized app for accessing the robotic car is designed to indicate predicted and real- time measured values of humidity and temperature. A sensor installed built- in helps in the measurement. The recurrent neural network (RNN) model is used to predict humidity and temperature. For this purpose, experiments are carried out in both outdoor and indoor settings. Accuracy of 85% and 90% is achieved in an outdoor environment and indoor setting