AI-Enhanced Wearable Devices and Smart PPE for Worker Monitoring

Leverage AI wearables and Smart PPE to enhance worker safety, understand applications, and navigate implementation challenges.

Course Description:

This intensive 2-day course is designed for leaders and managers seeking to understand the practical applications and strategic implications of these emerging technologies. Explore the landscape of smart safety devices, from sensor technology and connectivity options to AI-driven applications like fatigue monitoring, fall detection, and ergonomic analysis.

Gain insights into data handling, implementation challenges, ethical considerations like privacy and bias , and regulatory compliance. Equip yourself with the foundational knowledge to evaluate these technologies and foster a proactive, data-driven safety culture within your organization.

Who Should Attend:

• Occupational Safety and Health Manager
• Head of Operations Department
• Risk Manager
• Senior Project Manager
• Head of Division
• Senior Executive involved in strategic planning or compliance
• Logistics Manager

Course Objectives:

Knowledge Acquisition:

• Understand the core concepts of wearable technology, Smart PPE, and the Industrial Internet of Things (IIoT) in workplace safety.
• Recognize the primary benefits these technologies offer, including enhanced safety, improved compliance, and potential productivity increases.
• Identify the key enabling technologies involved: different sensor types, essential connectivity options, and power management considerations.
• Grasp the role of AI and Machine Learning in analyzing sensor data to provide actionable safety insights.
• Gain awareness of the relevant regulatory landscape.

Skills Development:

• Develop the ability to distinguish between various Smart PPE types (helmets, garments, etc.) and task-specific wearables (gas detectors, exoskeletons).
• Learn to identify common AI applications in worker safety, such as fatigue monitoring, fall detection, and ergonomic analysis.
• Gain insight into the concepts of edge vs. cloud data processing and the role of IoT platforms.
• Develop an understanding of the key factors influencing successful implementation, including cost, usability, accuracy, and connectivity challenges.
• Learn to recognize the critical ethical considerations regarding worker privacy, data security, consent, and algorithmic bias.

Practical Application:

• Apply knowledge to identify potential applications of AI-wearables and Smart PPE relevant to your specific industry context.
• Utilize understanding of implementation factors and ROI concepts to inform initial thinking about potential pilot projects.
• Interpret the value of safety dashboards and reporting concepts for operational monitoring and strategic improvement.
• Apply awareness of ethical and privacy issues to guide responsible technology adoption discussions within your organization.
• Consider emerging technology trends when evaluating the future potential of AI-wearables for enhancing safety culture.

What will I Learn From it:

• Identify how AI wearables enhance worker safety beyond traditional PPE.
• Understand the core benefits and applications of Smart PPE in your industry.
• Evaluate key technologies like sensors, AI, and connectivity for safety solutions.
• Recognize critical implementation factors including cost, user adoption, and ethics.
• Navigate the essential privacy and regulatory considerations for deployment.
• Leverage data concepts from wearables for proactive safety management discussions.
• Assess the potential ROI components of investing in AI-enhanced safety technologies.

Training Methodology

This course utilizes a dynamic and engaging approach, blending expert instruction with interactive learning.

Expect a mix of concise presentations, real-world case study analyses , facilitated group discussions, practical brainstorming activities , and targeted Q&A sessions.

The focus is on practical understanding and application, minimizing theoretical lectures to ensure relevance for busy leaders.

Requirement/
pre-requisites:

• No prior technical expertise or deep understanding of Artificial Intelligence is required.
• An interest in exploring how AI can be strategically applied to improve workplace safety and risk assessment is beneficial.