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A Framework For Green IoT Technologies On Agricultural Process Water and Air Remediation During Covid-19
NeuroQuantology ; 20(10):4049-4060, 2022.
Artigo em Inglês | EMBASE | ID: covidwho-2033478
ABSTRACT
The current pandemic situation has led researchers to rethink the conventional agricultural process. Nowadays, conventional agricultural processes are being replaced with an advanced Internet of Things (IoT)-based technology to reduce mass gathering in fields. Moreover, the advancement of technology is essential to feed the 7 billion people around the world. Thus, researchers developed several IoT devices that come under the Consumer IoT or CIoT devices which help the farmers to monitor farm performance and activities remotely. During the remote monitoring processes, the wireless CIoT devices gained privacy and security threats which became a major concern. Thus, besides gaining a competitive advantage in agriculture, minimising privacy and security threats is also essential in this pandemic. This research is going to understand the recent CIoT devices, their privacy and data protection approaches, challenges and mitigation strategies. The researchers have conducted secondary research using available journal articles and authentic internet sources belonging to the past five years. After that, other journal articles have been accessed as well to draw an effective discussion. Findings showed that privacy, data protection and security are the three major concerns that can be addressed by using an alternative wireless system. Blockchain and “Low-power Wide Area Network” are two other approaches that can be used as well. Other challenges include the cost of CIoT devices that can be addressed by purchasing low-cost sensors and microcontrollers.
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Texto completo: Disponível Coleções: Bases de dados de organismos internacionais Base de dados: EMBASE Idioma: Inglês Revista: NeuroQuantology Ano de publicação: 2022 Tipo de documento: Artigo

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Texto completo: Disponível Coleções: Bases de dados de organismos internacionais Base de dados: EMBASE Idioma: Inglês Revista: NeuroQuantology Ano de publicação: 2022 Tipo de documento: Artigo