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What are the major limitations of current environmental monitoring systems? 


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Current environmental monitoring systems face several limitations. Bioelectronic sensors are prone to durability issues, interference, power supply challenges, sensitivity to various environmental variables, data processing complexities, high costs, and biofouling risks . Conventional systems relying on manual sampling struggle with spatiotemporal coverage and real-time monitoring, hindering effective pollution management . Additionally, the deployment of existing monitoring stations in large cities is slow, costly, and energy-inefficient . To address these challenges, leveraging Internet of Things (IoT) technologies can offer scalable, cost-effective, and energy-efficient solutions for continuous and real-time environmental monitoring, enabling better pollution source identification and management . Nanomaterial-based electrochemical sensors show promise in enhancing sensitivity and selectivity for detecting trace pollutants, contributing to improved environmental safety .

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Current environmental monitoring systems have limitations such as slow deployment, large station sizes, and high maintenance costs, as highlighted in the paper on LoRa technology for environmental analysis.
Limitations of current environmental monitoring systems include insensitivity to trace pollutants, high costs, and inadequate real sample applicability, highlighting the need for improved nanomaterial-based electrochemical sensors.
Major limitations of current environmental bioelectronic sensors include durability issues, susceptibility to interference, power supply challenges, sensitivity to various signals, data processing complexity, high costs, and biofouling concerns.
Current environmental monitoring systems face challenges in data handling, connectivity, power usage, and system potential. IoT technology is proposed to address these limitations effectively in the presented research.
Current environmental monitoring systems have limitations due to manual sampling, sparse instrument deployment, and inability to track pollutants' spatiotemporal distribution, hindering timely pollution detection and management.

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