GASPRO International Journal of Eminent Scholars
Guides For Authors
- Call For Papers
- Processing Charges
- Journal Coverage
- Open Access Policy
- Terms and Policies
Trending Topics
Secured Payment

LEVERAGING AI-DRIVEN AUTOSTORE SYSTEMS TO ENHANCE EMERGENCY RESPONSE AND CRISIS MANAGEMENT; A FOCUS ON GROCERY STORES
ABSTRACT
While AI-driven Autosystem offers potential
solutions such as real-time inventory optimization, increased coordination, and
predictive analytics, its implementation in emergency response and crisis
management remains restricted. Many grocery stores have failed to properly
harness these technologies to solve crucial areas such as anticipating demand
for vital commodities, decreasing supply chain risks, and guaranteeing fair
disruption of resources during a crisis. This study investigates Leveraging
AI-Driven Autostore Systems to Enhance Emergency Response and Crisis
Management; a focus on Grocery stores. Descriptive statistics was
employed by the study in analyzing the collected data on the impact of
AI-driven Autostore systems on response to emergencies in disaster management.
The study established that an AI-driven Autostore system goes a long way in
helping to mitigate delays in the response to disasters or pandemic situations.
The study recommends that policymakers and industry stakeholders work together
to design supporting policies that promote the use of AI while adhering to the
proper ethics for guaranteeing data privacy and security. By taking a proactive
approach and developing public-private collaborations, food merchants can fully
realize the promise of Autostore’s AI-driven system for constructing resilient
supply chains and increasing their ability to serve communities during
catastrophes.
KEYWORD: Leveraging,
Ai-Driven Autostore, Emergency Response, Crisis Management and Grocery Stores
Download Article
Featured Article
.gif)
Global Studies Quaterly
Bioinformatics Advances
Bioscience & Technology
Latest Articles
ISSN(Hardcopy)
2630 - 7200
ISSN(Softcopy)
2659 - 1057
Impact Factor
5.693