Continuous monitoring of the industry setting is necessary to maintain efficiency of operations, safety, and predictive maintenance. The traditional industrial monitoring systems are highly dependent on localized sensors and human observation, which result in expensive installation, restricted coverage zone and could be unsafe to operators. The recent progress in the embedded systems, robotics, and low-cost sensors has made it possible to design the autonomous mobile robot able to conduct the industrial inspection tasks effectively. The present paper introduces the design, development, and testing of the low cost autonomous robot that could be used in the industrial monitoring technology. The suggested system incorporates inexpensive sensing sub-system, control architecture based on microcontrollers, wireless communication and autonomous navigation. Robot has the potential to check environmental conditions like temperature, humidity, gas content and vibration and also move freely within the industrial floors and relay real time statistics to a monitoring station. To be able to scale and be cost-effective, it adopts a modular hardware design and a layered software architecture. There are sensor fusion methods used in obstacle detection and navigation, and power-saving algorithms used in increasing battery life. Through experiment verification it is proved that above the developed robot has a sure monitoring performance with satisfactory accuracy at relatively low cost as compared to other standard industrial monitoring systems. The offered solution can be taken as an alternative to small- and medium-scale industries, which can enhance monitoring, safety, and reliability of operations by automating their tasks. It is rather economical and practical.
S. Verma, Naveen Kumar· International Journal of Mod...· 0 citations
Biosensors, or biotechnology-based sensors, have evolved from laboratory prototypes into key tools in healthcare diagnostics, food safety, environmental monitoring, industrial bioprocess control, and precision agriculture. They combine biological recognition elements—enzymes, antibodies, nucleic acids, aptamers, or cells—with transduction systems such as electrochemical, optical, piezoelectric, thermal, or magnetic mechanisms to detect biochemical interactions. Advances in nanotechnology, microfluidics, synthetic biology, wearable electronics, and data-driven analytics have improved biosensor performance by enabling lower detection limits, faster responses, multiplex detection, better function in complex samples, and support for point-of-care or at-home testing. Multiplex biosensors detect multiple biomarkers simultaneously using technologies like microarrays, barcoded nanoparticles, and multi-electrode arrays, which is valuable for diseases such as cancer and inflammatory disorders. Nanomaterials—including graphene, MoS₂, carbon nanotubes, metal-organic frameworks, plasmonic nanostructures, and engineered nanoparticles—enhance sensitivity by increasing surface area and improving signal transfer. Antifouling strategies such as PEGylation, zwitterionic coatings, and hydrogels maintain sensor performance in complex samples like blood, saliva, sweat, and wastewater. Wearable biosensors use flexible materials and epidermal electronics to continuously monitor analytes in sweat, tears, or interstitial fluid and connect wirelessly to smartphones through Bluetooth or NFC for real-time monitoring. Machine learning and AI improve data analysis, while CRISPR-based biosensors using Cas12 and Cas13 allow highly specific nucleic acid detection. Synthetic biology also enables programmable cell-based biosensors. In industrial biotechnology, biosensors monitor glucose, lactate, pH, dissolved oxygen, and product levels in real time to optimize process efficiency and yield. Environmental biosensors detect heavy metals, pesticides, endocrine-disrupting chemicals, and microbial contamination, often integrated with IoT networks. However, challenges remain in receptor stability, nanomaterial reproducibility, large-scale manufacturing, regulatory approval, AI transparency, and sustainable disposal of single-use sensors.
S. Verma· International Journal of Mod...· 0 citations
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