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Wireless Sensor Network (WSN)-based Automatic Weather Stations (AWSs) perform automatic collection and transmission of weather data. These AWSs face challenges, which lower their performance. Hence, a need for regular monitoring to reduce down time. We propose condition monitoring, comprised of a data receiver, analyser, problem classifier and reporter and visualizer, to mine data relationships, identify possible causes of problems and perform reporting of AWS status. The data receiver uses an M/M/1/k queuing model. We use Successive Pairwise REcord Differences (SPREDs) algorithm to compare arrival rates and packet content so as to establish sensor, node and AWS level performance. We also perform a hybrid of Grubb outlier detection and correlations amongst related variables for data validation. Problems take on one of four states. One connection can receive data at a rate as low as 1ms, without loss while problem identification especially in high density network is improved

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The changing climate has negatively impacted food systems by affecting rainfall patterns and leading to drought, flooding, and higher temperatures which reduce food production. This study examined the ability of communities to cope with food insecurity due to the changing climate in the Serere and Buyende districts, which are two different agro-ecological zones of Uganda. We administered 806 questionnaires to households, a sample size which was determined using Yamane’s formula, with the snowball sampling method used to select the households. The questionnaire sought information, including that regarding the respondents’ resources, the effects of climate change on households, and the coping mechanisms employed to reduce the impact of climate change on food security. The data collected was coded and analyzed using the statistical package for the social sciences (SPSS). Agriculture was found to be the main source of income for 42.4% of male adults and 41.2% of female adults in Serere. In Buyende, 39.9% of males and 33.7% of females rely on selling animal, poultry, and food crops. Aggregate results further showed that 58.3% of females and 42.2% of the males from both districts had suffered from the impacts of climate change, and that the effects were more evident between March and May, when communities experienced crop failure. The study further found that the percentage of households who had three meals a day was reduced from 59.7% to 43.6%, while the number of households with no major meals a day increased from 1.3% to 1.6%. We also found that 34.3% of households reported buying food during periods of crop failure or food scarcity. Moreover, despite reporting an understanding of several coping mechanisms, many households were limited in their ability to implement the coping mechanisms by their low incomes. This reinforced their reliance on affordable mechanisms, such as growing drought-resistant crops (32.7%), rearing drought-resistant livestock breeds (26.1%), and reducing the number of meals a day (14.5%), which are mechanisms that are insufficient for solving all the climate-related food insecurity challenges. We recommend that the government intervenes by revising policies which help farmers cope with the negative effects of climate change, promoting the sensitization of farmers to employing the coping mechanisms, and subsidizing agricultural inputs, such as resistant varieties of crops, for all to afford.

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