Fifth generation (5G), the next generation telecommunications will be striking the markets in near future. Device‐to‐device (D2D) communication would be a part of 5G to serve communication needs for billions of connected devices to support high data rate ultrareliable low latency communications. Indoor 5G will be relying on distributed small cell solutions and D2D along with machine‐to‐machine connections. Machine learning is one of the most promising tools for providing the best set of solutions to learn the influential scenarios and certain parameters of the communication networks. This research proposes reinforcement‐learning‐based latency controlled D2D connectivity (RL‐LCDC) algorithm and its Q‐learning approach in an indoor D2D communication network for strong 5G connectivity with minimum latency. The proposed approach, RL‐LCDC efficiently discovers the neighbors, decides the D2D link, and adaptively controls the communication range for maximum network connectivity. The results show that RL‐LCDC optimizes the connectivity with lower end‐to‐end delay and better energy efficiency with efficient convergence time when compared with other conventional schemes.

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Background In this pandemic of COVID-19, the highest amount of infective material, biomedical waste is generated in hospitals and it is frequently handled by the healthcare workers irrespective of cadres. Hence the awareness of healthcare workers in regards with biomedical waste (BMW) management is crucial in this pandemic. This study is therefore conducted to assess the knowledge, attitude and practices in BMW management among health care workers in our institution. Results A total of 280 subjects consisting of doctors, nursing staff and group D workers were included in the study after obtaining informed consent. The knowledge among healthcare workers was satisfactory, but comparatively group D workers were lagging behind. Overall they all have a good attitude towards BMW management but practices on BMW management needs improvement mostly among group D workers. Conclusions There have to be regular training programmes on biomedical waste management and its hazards for all the healthcare workers including group D workers. Along with educational intervention, strict implementation of biomedical waste management guidelines with its monitoring at all levels is also very much essential.

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