Frozen food is one of Bangladesh’s most valuable export items, comprising more than 80% of shrimp. The most cultivated area of shrimp is situated in the southern region of Bangladesh. This research was carried out to identify the core problem in the shrimp farming areas in order to support the related farmers in seeking a solution through the most common technology used by them. The study was conducted in Shyamnagar, Satkhira district with a total of 40 female respondents involved. This research showed that shrimp farming is pressurized by a lack of proper information on disease identification and its management. Mobile apps are considered the most common information providers among that community. The research defined the common problems and necessity through the system requirement specification (SRS) to provide needed details for the farmers that focused on mobile-app development eventually. It was found that disease (82.86%) and water quality (17.14%) are the most common issues while among the diseases White Spot Syndrome Virus and Yellow Head Virus Disease followed by Black Gill disease were the most alarming to handle without pre-management knowledge. The research also suggests developing voice-based mobile apps for shrimp farmers in the local language.

We collected paired measurements of indoor and outdoor PM2.5 concentrations at 17 homes in Dhaka, Bangladesh, to quantify indoor-outdoor levels, their spatio-temporal variations, and influencing factors. A pair of PurpleAir PM2.5 sensors were deployed at each home, one indoors and the other outdoors, during the wet (June to August 2021) and dry (December 2021 to February 2022) seasons, and the locally calibrated (against a beta attenuation monitor) and quality-assured data were used for analysis. Indoor and outdoor PM2.5 levels were three times higher during the dry season (indoor 146 ± 22 µg/m³, outdoor 153 ± 23 µg/m³) than during the wet season (indoor 52 ± 12 µg/m³, outdoor 50 ± 11 µg/m³). Indoor to outdoor (I/O) ratios were close to 1 in both seasons (dry: 0.97 ± 0.14, wet: 1.05 ± 0.19). This suggests that regional background pollution levels significantly influence indoor levels observed in different households. Higher infiltration factors (dry: 0.83 ± 0.12; wet: 0.87 ± 0.14), determined through mixed effect regression of parallel indoor and outdoor timeseries data, further highlight the substantial impact of outdoor pollution on indoor levels. Data from individual households exhibited strong temporal correlation between indoor and outdoor levels in both seasons (Pearson R: 0.82 ± 0.12 during the dry season and 0.83 ± 0.14 during the wet season), whereas indoor-outdoor spatial correlations across measured households were moderate (R: 0.49 and 0.62 during dry and wet seasons, respectively). These spatial correlations and empirical regression modeling suggest that while the spatial variation of outdoor PM2.5 levels significantly influences indoor levels' spatial variation, other factors such as indoor source activities and ventilation-related features play crucial roles in explaining variabilities in indoor PM2.5 across homes. Overall, our study suggests that indoor environments in Dhaka city are nearly as polluted as outdoor settings, and this locally derived scientific evidence can be valuable for enhancing public awareness and developing mitigation measures to reduce PM2.5 exposures in Bangladesh.