Marko Hännikäinen Tampere University of Technology IoT week CLOUD-BASED SERVICE PLATFORM FOR WIRELESS SENSOR NETWORKS

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1 Marko Hännikäinen Tampere University of Technology IoT week CLOUD-BASED SERVICE PLATFORM FOR WIRELESS SENSOR NETWORKS

2 Outline The WAPS project Development steps 1. Low-power wireless sensor networks 2. Interfaces 3. Platform for sensor services Pilot and demo cases Conclusions

3 WAPS project Wireless sensor networks: from technology to applications WAPS is part of Tekes Ubicom WAPS helps to adopt sensor networks in products and services WAPS project started in mid-2011 and lasts till end of 2013 Participants: Desagent Oy, Fidelix Oy, Cassidian Finland Oy, Espotel Oy, Fastrax Oy, Nordic ID Oy, Vaisala Oyj, Vexve Oy, VTS Kiinteistöpalvelu Oy, Tampere University of Technology

4 STARTING POINT: RESEARCH ON LOW-ENERGY WSN

5 TUTWSN Firmware SensorOS Luminanne Temperature Acceleration Self Diagnostics Positioning TUTWSN research work and PhD projects (2002-) Autonomous operation Multi-hop mesh networking Node movement, adding gateways and nodes Scalable network sizes (density and number of nodes) No single point of failure Multiple routes through network with cost-based traffic balancing Multiple gateway points Low power consumption Energy efficient MAC layer (low duty-cycle) Energy efficiency also in router nodes Low-cost implementation COST components Prototypes and pilot studies Sensors and actuators lux T G CO2 IR Applications SensorAPI Transfer Routing MAC Hardware abstraction layer Processors Radios

6 Main TUTWSN pilots Main pilot studies Nodes Duration Technology Sewer water level monitoring MHz Chemical factory monitoring GHz Green house temperature and humidity leveling GHz Campus network for teaching GHz Residential monitoring, several homes GHz Transportation cargo monitoring, several GHz Building automation monitoring, several GHz Environment (outdoors) monitoring, several MHz Environment conditions in cow house GHz Hospital personnel safety GHz

7 Motivation for WAPS project Need Real-time sensor data enables new services, productivity Investments which are not covered by a single app Solution A cloud-based service platform for cost-efficient (fast) implementation of sensor services Easy to adopt and customize, scalability for number of users and apps Utilizes wireless sensors, open data sources and existing sensor systems Status Prototype ready, pilots starting with companies

8 CLOUD-BASED SERVICE PLATFORM

9 Cloud-based service platform for wireless sensor networks Shared, multi-organization platform for implementing added-value and applications (the horizontal model) Interfaces, methods, examples for adopting cloud computing Processing of large data reserves and real-time measurements Pilots for new sensor data services Customers Vertical model Sales Service delivery Data processing Data storage Sensors Horizontal model Multiple: Customers Companies Services Delivery channels Data processing Sensor systems

10 10 WSN OpenAPI gateway implementation (available as open source software, implemented in WAS project) Wireless sensors Data systems ZigBee Bluetooth WirelessHART 6LoWPAN M2M Wirepas Mobile phones Technology adaptation WSN OpenAPI Gateway Database Data validation and fusion WSN OpenAPI Sensing Management Gateway Core Metadata Control Alarms WSN OpenAPI Technology adaptation Applications Back-office Process automation Building automation Health monitoring Security Cloud computing

11 Availability of WSN OpenAPI and OpenAPI Gateway

12 Service platform for wireless sensor networks (currently in Amazon EC2) Sensors, actuators Sensor node Embedded Gateway WSN networks (ZigBee, TUTWSN, proprietary) Gateway Gateway Amazon, Google, Microsoft, private cloud computing platforms Data processing for different applications Offloading computing to cloud Data processing Data processing Data storage Data Authentication storage Authorization Accounting Services Services (e.g., reports, alerts, control) Service deliver Service delivery System integration App stores Building automation Industrial automation Logistics Home networks Private clouds

13 PILOT SERVICES AND DEMOS

14 Pilot services and demos Residential energy monitoring service Online inventory services for RFID systems Cold chain logistics TETRA/TEDS-based services Demos and prototypes: Twittering flower pod, smart wardrobe, wireless weather station, mobile phones, embedded cloud with RasberryPis, SOM analysis,

15 Example: embedded cloud design for internet-of-things Devices use each others resources and move processing to the cloud The design consists of Process Description Language (PDL) Distributed MiddleWare (DiMiWa) Prototype: RasberryPi platforms with camera, wireless sensors, image pattern recognition

16 Example: Data mining with Self Organising Map Analysis of measurements for detecting abnormal/nonoptimal situations Example: samples collected within 2 months in one apartment

17 MMEA platform Measurement, Monitoring and Environmental Efficiency Assessment Demonstration: Services for environmental monitoring Wireless local weather station Phones as sensors Wireless sensor networks (several technologies) Building automation systems WAPS Sensor data services Open data

18 Pilot service: RealEco Residential energy consumption: electricity, water, heating Indoor/outdoor temperatures, CO2, humidity, other conditions Monitoring and controlling of household appliances Alarms for abnormal situations Interfaces to social networks, competitions among users

19 CONCLUSIONS

20 Conclusions Development of a shared platform to create and experiment large and small services Pilots starting with industry partners Results and commercialization by the end of 2013

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