IOT a senzorika v praxi. Watson Solution Market. Miroslav Iwachow CEE Technical Leader Industry Sector, IBM

Transcription

1 IOT a senzorika v praxi Watson Solution Market Miroslav Iwachow CEE Technical Leader Industry Sector, IBM 1

2 Agenda Customer s Perception IoT Opportunity Assessment Workshop IoT is just a bunch of sensors. Right? Solution Requirements What should focus on? How about Worker Safety? Our Solution Proposal Conclusion

3 Client Perception It s not for us I don t know? what is it? We already collect data Perception We run reports and analysis of data offline We can t use IoT for our staff privacy issues It s too complex to build or the cool stuff on youtube is not for us. Solution Understanding the Industry find a pain point build a solution It s not what you collect but how you present ; The right insight at the right time Watson Analytics Value is derived by interpreting data for actionable insight Privacy can be addressed by application design and tailored to local legislation IBM has a framework to collect, store, analyze as well as create and run applications and dashboard IoT is just mountains of data we can t afford to store We can download apps to our iphone and run Google Map and Wise, Man-down, - that s IoT right How will we scale to tens of thousands devices OK We want to do IoT what should we do There are different ways to approaching data like Cloud, Streams and Edge computing. Here lie to privacy issues, the ownership of data, your differentiation to the competition IBM can help with a cloud platform that scales and different architectures to address different scales of projects Lets run a discovery workshop for you and your industry

4 IBM and IDC jointly identified 10 use cases based on size, analytics penetration, and industry variety IoT Use Cases Enabled by Cognitive Systems 1. Construction Machinery Management 2. Distribution Automation (Electricity) 3. Freight Monitoring 4. Infrastructure (Smart Buildings) 5. Insurance Telematics 6. Manufacturing Operations 7. Omni-Channel Operations 8. Production Asset Management 9. Public Safety and Emergency Response 10. Smart Meters (Electricity) Monitoring & maintaining heavy machinery assets, regularly assessing asset conditions and remotely diagnosing asset failure Non-smart meter field devices owned by the electric utility used to control & optimize power flow to ensure safe & reliable service System carries out intelligent recognition, location, tracking and cargo monitoring through real-time communication (Air, Rail, Land, Sea) IoT technology using advanced automation to optimize operations and maintenance, adapting real-time to internal policies & external signals IoT technology for usage based insurance offerings for autos. For both consumer & business clients Intelligent & interconnected I/O tools to enable autonomous exchange of information in different components, trigger actions and control independently Evolution of multi-channel retailing to meet customer demand across multiple platforms and operations to deliver seamless customer experience Maintain industrial devices linked to production value chain, assess equipment conditions and remote diagnosis i.e. predictive maintenance Predict, prevent and reduce crime; address new emerging threats; improve emergency response, and allocate resources effectively (Fire, Police, EMS) Smart metering systems use solid-state meters for billing, power quality, & power outage purposes. Source: IDC Market Analysis, July

5 Connected Car Use Cases

6 Warehouse Personal Safety

7 A Real Use Case Workplace injuries and illness cost the US $190 billion annually $55.4 billion direct costs 27M working days lost 4,628 Fatal work injuries Wearables technologies presents a new opportunity for reducing workplace death and injuries Non intrusive, enabling hands-free work Always-on Employee- and environment-aware Connected Attention-getting

8 Avoid Getting Struck by Forklift? Let s just pick one

9 What kind of Architecture - IoT Architecture with Gateways (Edge) Sensors Real-time Analytics Operational Analytics Big Data Analytics Gateways for local analytics Watson IoT Platform Real-time analytics Streams/Spark Streaming Sensor Data History BigInsights / DashDB / Identity Insights / Watson Hadoop / Big Data analytics / Context Computing (no gateway) Publish / Subscrib e low latency local real time analytics Local aggregation to reduce bandwidth for data transformation to cloud Local rolling window historian for local query Informix / Cloudant / IoT Foundation Service / TimeSeries Service REST, NoSQL, Relational, Timeseries, Spatial storage & Operational Analytics Informix Warehouse Accelerator In-memory Analytics SoftLayer / BlueMix Cloud infrastructure SPSS / Cognos / PMQ Predictive analytics and dashboard = IBM products = IBM Database

10 IBM Worker Safety Solution The solution sensors and applications works as your personal protective application. It allows intuitive specification of shields that govern the personal wellness and safety of their owner, detect hazard and notify employees and supervisors BLE/ANT+ / CPU Accelerometer: Speed-X Speed-Y Speed-Z Hazards Detection Alert Employee Inform Supervisor and Emergency Center Environmental-sensing: temperature light noise oxygen deficiency carbon monoxide Location: GPS Wifi Beacons Bio-sensing: heart-rate Body temperature Excessive lifting, pushing, carrying Fatigue Alertness Dehydration Fall / Injury Use of safety equip Broadcast message to nearby employees IBM Worker Safety Solution Federated Analytics Detective (real-time) / Predictive 10

11 Use Case Worker Proximity Counter Driver awareness of workers in the vicinity Driver sees on display the number of people in the vicinity of the MHE. He evaluates no one directly in front of him, looks left and right sees #333 is on the right. Missing person must be directly behind him or hidden by pallet. Count has increased suddenly from 2 to 3. Looking around he sees #222 is entering his safety zone Caution is warranted. Survey area to find the hazards before moving on. Person moving or standing, and lots of data for back end analysis Respects rules of no mobile strategy and uses simple and very affordable devices for large scale deployment and compensate with and additional back end analytics and can grow to additional use cases as needed Smart Beacon Broadcast: UUID #111 movement yes battery strength 50% Blind spot Gray zone Gray zone Smart Beacon Broadcast: UUID #333 movement No battery strength 50% Smart Beacon Broadcast: UUID #222 movement yes battery strength 90% Field of view 11

12 Use Case Proximity and Count Driver Floor Manager possible views Backend Analytics possible view Display or LED for the number of people in safety zone & audible tone when number changes location estimation of each MHE Number & id of people in vicinity of an MHE MHE Real Time Proximity Statistics worker density near MHE worker density per tasks * Alert when a large number of workers is close to one MHE for extended periods of time MHE Proximity Statistics worker density -time of day worker density per tasks* Trends Heat map of busy areas Heat map of peak times and worker Statistics of workers that approach MHE and time spent in vicinity Other KPI and historical analysis * * Future integration points 12

13 MHE & Warehouse Operators Collision preventions Driver Notification Sound /text to speech Notifications Led indications Driver Wearable Driver Activity Driver Heart rate Proximity Sensor / Depth Camera Tracks proximity to objects Q B Bluetooth BLE BLE, broadcast BLE, broadcast BLE, broadcast Quantum Box - BLE Bluetooth wifi MQTT HTTPS - Sensors: temp Humidity Movement - Real time analytics - Connectivity to Driver wearable Smart Beacons - LED display: for Alerts and Notifications proximity to objects number of worker near me Wifi MQTT / HTTPS 1. IOTP 2. Data storage 3. Real time Analytics 4. Offline Analytics 5. Indoor location Optional MQTT / HTTPS/ Push HTTPS/REST Smart Beacon Broadcast: UUID movement battery strength Drivers Fatigue Test App Supervisor App Near misses Heat Maps Dashboard

14 Solution Architecture Driver Wearables Mobile Backend (BlueMix) Analytics (Bluemix) Quantum Box Sensors WorkRight Quantum Box Realtime Analytics Push Notification WorkRight Backend Cloudant Aggregated Data & WorkRight Data Heats maps Dashboard Smart Beacons IOTF Object Storage Save All Data Offline analytics/ Big data Jupyter Notebook Supervisor ios App Dashboard WorkRight Realtime Analytics Spark Mathlab

15 Sample Customized Screens of Application Supervisor View

16 A Sample Architecture IoT for Manufacturing 23 Plant Analytics evaluates equipment status and operations and provides predictions on equipment issues 5 Visualizations are immediately updated displaying predictions and prescriptions on how to resolve problems Prescriptive Maintenance Quality Analytics Warranty Analytics Plant Performance Analytics Bluemix 2 Data comes in through Watson IoT Platform 2 Edge IIB + Messagesight Direct PMQ (local) 5 Action prescriptions are delivered to maintenance personnel or issue work order into EAM system Maximo CE Warranty Tririga 1 Sensors and manufacturing systems are connected to transmit live information 1 -Robots -Equipment -Machines -Tools Existing Systems

17 Conclusions Research the Pain Point, Business Case and Issues before you start There is more than one solution to every problem Different sensors Different costs Combine data for more complex insights The solution is the Processes, Applications and Analytics not the DATA Focus on the Use Case and what benefit competitive advantage it brings Think change the way you work Process Provide Insight not data Provide a method of presenting the data The same data may be presented in different ways to different people A framework is important since the number of sensors will increase as you add more use cases and being able to integrate them quickly will be a competitive advantage