Vol 14 Issue 2 April 2026-June 2026

Abstract: Organizations deploying AI inference systems for knowledge-work automation currently lack a shared, intuitive vocabulary for capacity planning and procurement. Existing metrics — tokens per second, FLOPS, benchmark scores — carry precise technical meaning but fail to communicate operational impact to the managers and executives who make infrastructure investment decisions. This paper introduces a dual-metric framework that addresses this gap. The first metric, Desk Power (DP), quantifies the economic replacement capacity of an AI server in terms of equivalent human office workers, drawing explicit analogy to James Watt's mechanical horsepower. The second metric, Concurrent Human-Speed Workflows (CHW), quantifies the number of simultaneous users or workflow streams a given system can serve at or above a specified responsiveness threshold. Together, DP and CHW answer the two questions that drive real procurement decisions: how many employees can this system replace (DP), and how many employees can it serve at once (CHW). A formal mathematical framework is developed for both metrics, incorporating token generation rate, system availability, parallelism, quality correction, and response-speed thresholds. Worked examples are provided for systems ranging from local consumer-GPU edge nodes to enterprise multi-GPU clusters. The proposed framework offers a vendor-neutral, audience-appropriate language for AI capacity planning, workforce transition analysis, and regulatory impact assessment.

Keywords: AI capacity measurement, large language models, office automation, workforce displacement, inference throughput, concurrent users, server sizing, decision-making framework.

Title: Desk Power and Concurrent Human-Speed Workflows: A Dual-Metric Framework for AI Infrastructure Decision-Making

Author: Eng. Nawaf F. Al-Mutairi

International Journal of Engineering Research and Reviews

ISSN 2348-697X (Online)

Vol. 14, Issue 2, April 2026 - June 2026

Page No: 10-16

Research Publish Journals

Website: www.researchpublish.com

Published Date: 27-May-2026

Abstract: In recent years, the increasing incidents of theft and loss of personal belongings have created a strong demand for intelligent and automated security systems. Conventional bags lack real-time tracking, tamper detection, and emergency response mechanisms, making them highly vulnerable in crowded environments such as public transportation, educational institutions and travel scenarios. The Internet of Things has emerged as a transformative technology that enables physical devices to communicate and exchange data over networks, thereby enhancing system intelligence and responsiveness. “IoT enables real-time monitoring and tracking of assets through interconnected smart devices” [1]. The proposed IoT-based smart security bag integrates GPS tracking, GSM communication, camera-based monitoring, and tamper detection to provide a multi-layered  security system. “Multi-layered security architectures improve system robustness by combining detection, alerting, and prevention mechanisms” [2]. The system also incorporates cloud storage for remote accessibility and data persistence. This paper presents a comprehensive design and analysis of the proposed system, highlighting its advantages over existing solutions and demonstrating its effectiveness in improving personal and baggage security.

Keywords: IoT, GPS, GSM.

Title: IoT Based Smart Security Bag

Author: Rushika Bobade, Parth Vanarase, Kamil Sayyed, S.D.Lokhande

International Journal of Engineering Research and Reviews

ISSN 2348-697X (Online)

Vol. 14, Issue 2, April 2026 - June 2026

Page No: 1-9

Research Publish Journals

Website: www.researchpublish.com

Published Date: 26-May-2026