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The lifespan of wireless sensors networks (WSN) is entirely dependent on the energy level in sensors. To reduce the energy consumption, the traffic exchange between sensor nodes must be reduced in order to preserve the remaining energy. To reduce the network traffic overhead and prolong the lifespan of the network, we can use mobile agents to gather data from source nodes. However, this solution can be expensive in terms of delivery latency. For that we propose a new energy protocol named Energy Efficient Clustering with Mobile Agents (EECMA) based on combining the two paradigms of client/server and mobile agent to achieve the trade-off between increasing the network lifetime and reducing the data delivery latency. Furthermore, we expose a multidimensional model to process incoming data from sinks in order to enhance the overall performance of our system.

Governments can use social media platforms such as Twitter to disseminate health information to the public, as evidenced during the COVID-19 pandemic [Pershad (2018)]. The purpose of this study is to gain a better understanding of Canadian government and public health officials’ use of Twitter as a dissemination platform during the pandemic and to explore the public’s engagement with and sentiment towards these messages. We examined the account data of 93 Canadian public health and government officials during the first wave of the pandemic in Canada (December 31, 2019 August 31, 2020). Our objectives were to: 1) determine the engagement rates of the public with Canadian federal and provincial/territorial governments and public health officials’ Twitter posts; 2) conduct a hashtag trend analysis to explore the Canadian public’s discourse related to the pandemic during this period; 3) provide insights on the public’s reaction to Canadian authorities’ tweets through sentiment analysis. To address these objectives, we extracted Twitter posts, replies, and associated metadata available during the study period in both English and French. Our results show that the public demonstrated increased engagement with federal officials’ Twitter accounts as compared to provincial/territorial accounts. For the hashtag trends analysis of the public discourse during the first wave of the pandemic, we observed a topic shift in the Canadian public discourse over time between the period prior to the first wave and the first wave of the pandemic. Additionally, we identified 11 sentiments expressed by the public when reacting to Canadian authorities’ tweets. This study illustrates the potential to leverage social media to understand public discourse during a pandemic. We suggest that routine analyses of such data by governments can provide governments and public health officials with real-time data on public sentiments during a public health emergency. These data can be used to better disseminate key messages to the public.

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