Recommendations for a More Economically Viable and Secure Crowdsensing Environment

Mohannad Alswailim

Received: 2025-03-27, Published: 2025-03-28

Licence

This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

Disclaimer:
This article was originally published by Qassim University and was migrated to Scientific Scholar after the change of Publisher.

Abstract

This scientific paper examines crowdsensing security and economic issues. The study focuses on Artificial intelligence (AI), blockchain, and cryptography. By analyzing their effects, this paper shows how these technologies increase crowdsensing security and economic sustainability. AI-enabled algorithms improve crowdsensing data processing and decision-making. AI methods help stakeholders make educated decisions by extracting key insights from crowdsourcing data. Data integrity, trustworthiness, and privacy in crowdsensing platforms depend on blockchain technology. By securing conversations and sensitive data, encryption improves security. This article emphasizes crowdsensing system economics, including cost-effectiveness, scalability, and revenue creation. AI in data analysis helps generate market insights, improve service quality, and drive innovation. Blockchain technology enables transparent, auditable transactions, providing new revenue streams. In conclusion, integrating AI, blockchain, and encryption, is critical for tackling crowdsensing security and economic concerns. The findings offer recommendations for stakeholders, researchers, and policymakers on how to properly harness these technologies in order to ensure secure and economically sustainable crowdsensing ecosystems.