An Efficient Fuzzy C-Means Method with Variable FV-TC for Data Sensitivity Calculation in a Cloud Computing Environment

,; Dubey, Ashutosh Kumar

doi:10.35940/ijeat.a1760.109119

Cited by 2 publications

(1 citation statement)

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“…T Multiple Criteria Decision Making (MCDM) models and fuzzy synthesised choices are the foundation of several service choosing methodologies. [21]he findings we have acquired to assess our choice of services offered by the cloud indicated that our model outperforms previous MDMC approaches like TOPSIS, WPM, and the original AHP [17], captures the BDTP extremely well, guarantees Big Data QoS, and scales with the growing number of cloud providers. Through a variety of cloud services from several CSPs, WPM, the SAW, and imposed QoS requirements of Big Data workflows were used [16].…”

Section: International Journal On Recent and Innovation Trends In Com...mentioning

confidence: 92%

Evaluation of Garbage Management Based on IoT

Naveen Raja S.M

2023

IJRITCC

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Smart Waste Monitoring: To track the amount of waste in bins and containers, IOT-enabled garbage management systems use sensors and connected devices. These sensors can communicate real-time data to a centralized monitoring system and can identify the fill level. This data aids in streamlining waste collection routes, cutting back on pointless pickups, and enhancing garbage management effectiveness as a whole. Effective Resource Allocation: By giving precise data on waste generation patterns and trends, IOT-based garbage management systems enable optimal resource allocation. This information can be used by municipal authorities to make well-informed decisions on waste collection schedules, resource deployment, and staffing levels. IOT-based waste management solutions have the potential to make trash management procedures more effective and efficient while also being more affordable. The best garbage collection routes, operational cost reductions, and resource utilization may all be achieved with the aid of research into the best deployment strategies for IOT sensors and devices. Environmental Impact and Sustainability: Research Objective: Clearly identify the research objective, for example, by assessing how well IOT-based garbage management systems gather waste and allocate resources. Data gathering: Compile pertinent information on the methods used for trash generation, collection, and resource use. On-site observations, employee interviews, and database access for waste management operations are all effective ways to accomplish this. Gather information on IOT sensor technologies and their capabilities as well. Taken As alternative for Smart Waste Bins, Waste Level, Sensors, AI Recycling, Robots, E-Waste Kiosks. Taken for Evaluation preference is Reliability, Mobility, Service Continuity, User Convenience., and Energy Efficiency. Smart Waste Bins has performed more when compare to with other Real-Time Monitoring: The Internet of Things (IOT) can be used in waste management to enable real-time monitoring of trash cans or bins can be used to enhance garbage sorting procedures. Smart bins with cameras and sensors can automatically recognize and sort various types of rubbish. These smart bins can identify and categorise rubbish by utilizing IOT technology. on their material composition or recycling category.

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Section: International Journal On Recent and Innovation Trends In Com...mentioning

confidence: 92%