A reliable approach to customizing linux kernel using custom build tool-chain for ARM architecture and application to agriculture

ARM processors are receiving more attention as per IoT customized devices are concerned. A novel framework design tool for Linux kernel customization on ARM architecture has been illustrated. The tool is best suit from ARM based platformss like Raspberry pi, Beagle Bone, Intel Edison etc. The proposed techniques uses different tool chains for the kernel customization. The paper represents an integral framework that integrates all the cross compiling tools and simplifies the overall process. The framework has been used for the development of a customized kernel for Raspberry Pi on Ubuntu 14.04 host computer. The custom kernel has been ported in to Raspberry Pi and the performance evaluation has been done. Furthermore, the analysis aims to help users choose and configure their tracers based on their specific requirements to reduce their overhead and get the most of out of them. The testing of customized OS with raspberry Pi device in the field of agriculture. The smart node/mote is designed based on it to deploy in the agriculture field to test its feasibility. The group of nodes data is gathered using ThingSpeak cloud server. The gathered sensory data is analyzed and forecast on farmer’s mobile phone in the form of APP or handheld device for farmer

Risk of secondhand smoke exposure and severity of COVID-19 infection: multicenter case–control study

IntroductionExposure to secondhand smoke (SHS) is an established causal risk factor for cardiovascular disease (CVD) and chronic lung disease. Numerous studies have evaluated the role of tobacco in COVID-19 infection, severity, and mortality but missed the opportunity to assess the role of SHS. Therefore, this study was conducted to determine whether SHS is an independent risk factor for COVID-19 infection, severity, mortality, and other co-morbidities.MethodologyMulticentric case–control study was conducted across six states in India. Severe COVID-19 patients were chosen as our study cases, and mild and moderate COVID-19 as control were evaluated for exposure to SHS. The sample size was calculated using Epi-info version 7. A neighborhood-matching technique was utilized to address ecological variability and enhance comparability between cases and controls, considering age and sex as additional matching criteria. The binary logistic regression model was used to measure the association, and the results were presented using an adjusted odds ratio. The data were analyzed using SPSS version 24 (SPSS Inc., Chicago, IL, USA).ResultsA total of 672 cases of severe COVID-19 and 681 controls of mild and moderate COVID-19 were recruited in this study. The adjusted odds ratio (AOR) for SHS exposure at home was 3.03 (CI 95%: 2.29–4.02) compared to mild/moderate COVID-19, while SHS exposure at the workplace had odds of 2.19 (CI 95%: 1.43–3.35). Other factors significantly related to the severity of COVID-19 were a history of COVID-19 vaccination before illness, body mass index (BMI), and attached kitchen at home.DiscussionThe results of this study suggest that cumulative exposure to secondhand cigarette smoke is an independent risk factor for severe COVID-19 illness. More studies with the use of biomarkers and quantification of SHS exposure in the future are needed