I’m often asked, why do we create whimsical yet curated names for technologies, IoT, IoE, IIoT and so on, though I’m not the one who coined it, but I’m obliged to answer as that’s my bread & butter.
I feel in the next 10-20 years, IoE will surpass IoT by creating interconnected ecosystems that integrate people, processes, data, and things, enabling smarter, adaptive, and predictive environments. This holistic approach will improve decision-making, optimize complex systems, and enhance user experience, making IoT’s device-centric model less impactful in comparison.
Still don’t agree and feel they both are the same?, let me explain you with some examples how do they differ in right from the ideation to usage to analytics
Ideation: Scope & Integration
- IoT Approach: A smart thermostat in a home connects to the internet to adjust the temperature based on pre-set schedules or sensor readings.
- IoE Approach: In a smart building, thermostats, lighting, security systems, and occupancy sensors communicate with each other. When someone enters a room, the lights automatically adjust, the temperature is optimized, and even the security cameras switch to indoor monitoring modes. This integration ensures both comfort and energy efficiency.
Imagine a smart fridge that’s too smart for its own good. It detects you’ve run out of ice cream and automatically orders 5 tubs. But instead of delivering them gradually, they all show up at once, leaving you buried in ice cream, while the fridge smugly alerts you, “Stock level replenished.” that’s vanilla IoT.
Data Utilization and Analysis
- IoT Approach: A wearable fitness tracker monitors heart rate and steps taken, displaying this data on a mobile app.
- IoE Approach: In a connected healthcare ecosystem, data from wearable devices is sent to a patient’s medical team and combined with other data sources (e.g., medical records, environmental factors). Doctors can get alerts if a patient’s heart rate is abnormal and intervene earlier, leading to more proactive and personalized healthcare.
Re-imagine this with an IoE-powered smart home ecosystem. It knows you’re trying to eat healthy, so it coordinates the fridge, TV, and wearable fitness tracker to support your goals. But then, one Friday night, the fridge texts your TV, which starts showing salad commercials, while your fitness tracker vibrates every time you reach for a snack. The system even changes the lights to a soft green to remind you of your “healthy commitment.” Finally, exhausted, you whisper, “Just one cookie?” only for the home to respond through your speaker, “Put. It. Down.” that’s the beauty of IoE
Situational Segmentation of Contextual Data
- IoT Approach: A voice-activated speaker allows users to control smart home devices like lights and speakers.
- IoE Approach: In a smart home, the system learns users’ habits and preferences. It might automatically play calming music when someone arrives home from a long day, or adjust lighting based on individual preferences. This personalized experience adapts to the user’s lifestyle rather than requiring manual commands.
Application of Machine Learning and AI
- IoT Approach: A security camera with AI can detect motion and send alerts when there is activity in a restricted area.
- IoE Approach: In a smart city surveillance system, multiple cameras across locations are integrated with AI and machine learning to analyse activity patterns, detect potential threats, and coordinate with emergency services. If suspicious activity is detected, police units are automatically dispatched to the location, improving public safety.
This resonates how M2M developed into full fledged IoT and now the concept is taken over by IoE, read more what was written roughly 9 years ago here,
https://www.linkedin.com/pulse/compare-iot-m2m-why-dadheech-girish/
