Performance evaluation of energy-autonomous sensors using power-harvesting beacons for environmental monitoring in internet of things (IoT)

Sensors (Switzerland)

Volumn 18, Issue 6, 2018, Pages

  Dan Moiş, George ^a   Sanislav, Teodora ^a   Folea, Silviu Corneliu ^a   Zeadally, Sherali ^b  

^a TECHNICAL UNIVERSITY OF CLUJ NAPOCA   (Romania)

^b UNIVERSITY OF KENTUCKY   (United States)

Author keywords

Air quality; Bluetooth low energy; Energy harvesting; Environmental monitoring; Low power electronics

Indexed keywords

AIR QUALITY; BLUETOOTH; DATA ACQUISITION; EMBEDDED SYSTEMS; ENERGY EFFICIENCY; ENERGY HARVESTING; LOW POWER ELECTRONICS; PARTICLES (PARTICULATE MATTER); SCHEDULING ALGORITHMS; SENSOR NODES; VOLATILE ORGANIC COMPOUNDS;

BLUETOOTH LOW ENERGIES (BLE); BLUETOOTH LOW ENERGIES (BTLE); COMMUNICATION TECHNOLOGIES; CYBER PHYSICAL SYSTEMS (CPSS); ENVIRONMENTAL MONITORING; ENVIRONMENTAL MONITORING SYSTEM; FINE PARTICULATE MATTER (PM2.5); INTERNET OF THINGS (IOT);

INTERNET OF THINGS;

EID: 85047767250     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s18061709     Document Type: Article

References (51)

1. Lazarescu, M.T. Design and Field Test of a WSN Platform Prototype for Long-Term Environmental Monitoring. Sensors 2015, 15, 9481-9518.
2. Yang, Y.; Zheng, Z.; Bian, K.; Song, L.; Han, Z. Real-Time Profiling of Fine-Grained Air Quality Index Distribution Using UAV Sensing. IEEE Internet Things J. 2017, 5, 186-198.
3. World Health Organization. 7Million Premature Deaths Annually Linked to Air Pollution. News Release. 2014. Available online: http://www.who.int/mediacentre/news/releases/2014/air-pollution/en/ (accessed on 20 April 2018).
4. Dulebenets, M.A.; Moses, R.; Ozguven, E.E.; Vanli, A. Minimizing Carbon Dioxide Emissions Due to Container Handling at Marine Container Terminals via Hybrid Evolutionary Algorithms. IEEE Access 2018, 5, 8131-8147.
5. IPCC. Climate Change 2014: Synthesis Report. In Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; Core Writing Team, Pachauri, R.K., Meyer, L.A., Eds.; IPCC: Geneva, Switzerland, 2014; p. 151.
6. Justino, C.I.L.; Duarte, A.C.; Rocha-Santos, T.A.P. Recent Progress in Biosensors for Environmental Monitoring: A Review. Sensors 2017, 17, 2918.
7. Aponte-Luis, J.; Gómez-Galán, J.A.; Gómez-Bravo, F.; Sánchez-Raya,M.; Alcina-Espigado, J.; Teixido-Rovira, P.M. An EfficientWireless Sensor Network for IndustrialMonitoring and Control. Sensors 2018, 18, 182.
8. Sanislav, T.; Mois, G.D.; Folea, S.; Miclea, L. Integrating wireless sensor networks and cyber-physical systems: challenges and opportunities. In Cyber-Physical System Design With Sensor Networking Technologies; Zeadally, S., Jabeur, N., Eds.; The Institution of Engineering and Technology (IET): London, UK, 2016; pp. 47-76, ISBN 978-1-84919-824-0.
9. Harris, M. Mules on a mountain. IEEE Spectr. 2016, 53, 50-56.
10. Zeadally, S.; Khan, S.; Chilamkurti, N. Energy-efficient Networking: past, present, and future. J. Supercomput. 2012, 62, 3.
11. Hosen, A.S.M.S.; Cho, G.H.; Ra, I.-H. An Eccentricity Based Data Routing Protocol with Uniform Node Distribution in 3D WSN. Sensors 2017, 17, 2137.
12. Han, R.; Yang,W.;Wang, Y.; You, K. DCE: A Distributed Energy-Efficient Clustering Protocol forWireless Sensor Network Based on Double-Phase Cluster-Head Election. Sensors 2017, 17, 998.
13. Vaquerizo-Hdez, D.; Muñoz, P.; R-Moreno, M.D.; Barrero, D.F. A Low Power Consumption Algorithm for Efficient Energy Consumption in ZigBee Motes. Sensors 2017, 17, 2179.
14. Mouapi, A.; Hakem, N. A New Approach to Design AutonomousWireless Sensor Node Based on RF Energy Harvesting System. Sensors 2018, 18, 133.
15. Baranov, A.M.; Somov, A.; Spirjakin, D.; Bragar, A.; Karelin, A. RF Powered GasWireless Sensor Node for Smart Applications. Proceedings 2017, 1, 575.
16. Shaikh, F.; Zeadally, S. Energy Harvesting in Wireless Sensor Networks: A Comprehensive Review. Renew. Sustain. Energy Rev. 2016, 55, 1041-1051.
17. Mois, G.; Folea, S.; Sanislav, T. Analysis of Three IoT-Based Wireless Sensors for Environmental Monitoring. IEEE Trans. Instrum. Meas. 2017, 66, 2056-2064.
18. Guillemin, P.; Friess, P. Internet of Things strategic researchroadmap. In Internet of Things-Global Technological and Societal Trends From Smart Environments and Spaces to Green ICT; River Publishers: Gistrup, Denmark, 2011.
19. Guo, H.; Guo, A.; Gao, Y.; Liu, T. Optimization of a VOC Sensor with a Bilayered Diaphragm Using FBAR as Strain Sensing Elements. Sensors 2017, 17, 1764.
20. United States Environmental Protection Agency. Technical Overview of Volatile Organic Compounds. Available online: https://www.epa.gov/indoor-air-quality-iaq/technical-overview-volatile-organic-compounds (accessed on 20 April 2018).
21. Folea, S.C.; Mois, G. A Low-PowerWireless Sensor for Online Ambient Monitoring. IEEE Sens. J. 2015, 15, 742-749.
22. Benammar, M.; Abdaoui, A.; Ahmad, S.H.; Touati, F.; Kadri, A. A Modular IoT Platform for Real-Time Indoor Air Quality Monitoring. Sensors 2018, 18, 581.
23. Gas Sensing Solutions Limited. CozirTM Ultra Low Power Carbon Dioxide Sensor; Gas Sensing Solutions Limited:Dublin, Republic of Ireland, 2016.
24. ams AG. CCS811 Gas Sensor Solution Ultra-Low Power Digital Gas Sensor for Monitoring Indoor Air Quality; ams AG: Premstaetten, Austria, 2018.
25. Bosch Sensortec. BME680 Low Power Gas, Pressure, Temperature & Humidity Sensor; Bosch Sensortec:Reutlingen/Kusterdingen, Germany, 2017.
26. Cypress Semiconductor. CYBLE-022001-00 EZ-BLETM PRoCTM Module; Cypress Semiconductor: San Jose, CA, USA, 2017.
27. Sensirion. Datasheet SHT21 Humidity and Temperature Sensor IC; Sensirion: Staefa, Switzerland, 2011.
28. Texas Instruments. OPT3001 Ambient Light Sensor (ALS); Texas Instruments: Dallas, TX, USA, 2017.
29. Kim, J.Y.; Chu, C.H.; Shin, S.M. ISSAQ: An Integrated Sensing Systems for Real-Time Indoor Air Quality Monitoring. IEEE Sens. J. 2014, 12, 4230-4244.
30. Manes, G.; Collodi, G.; Gelpi, L.; Fusco, R.; Ricci, G.; Manes, A.; Passafiume, M. Realtime Gas Emission Monitoring at Hazardous Sites Using a Distributed Point-Source Sensing Infrastructure. Sensors 2016, 16, 121.
31. Velasco, A.; Ferrero, R.; Gandino, F.; Montrucchio, B.; Rebaudengo, M. A Mobile and Low-Cost System for Environmental Monitoring: A Case Study. Sensors 2016, 16, 710.
32. Zeng, Y.; Xiang, K. Adaptive Sampling for Urban Air Quality through Participatory Sensing. Sensors 2017, 17, 2531.
33. Ng, C.-L.; Kai, F.-M.; Tee, M.-H.; Tan, N.; Hemond, H.F. A Prototype Sensor for In Situ Sensing of Fine Particulate Matter and Volatile Organic Compounds. Sensors 2018, 18, 265.
34. Broday, D.M.; the Citi-Sense Project Collaborators. Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement-The Promise and the Current Reality. Sensors 2017, 17, 2263.
35. Bosch Press Release. “PlantectTM” Smart Agriculture Solutions-Bosch Launches Innovative Disease Prediction Service Using Sensors and Artificial Intelligence. Available online: http://www.bosch.co.jp/ press/rbjp-1706--05/?lang=en (accessed on 20 April 2018).
36. Libelium Comunicaciones Distribuidas S.L. Libelium-SensorInsight Air Quality Index Solution Kit. Available online: https://www.the-iot-marketplace.com/libelium-sensorinsight-solution-kit#hardware-components (accessed on 20 April 2018).
37. Srbinovski, B.; Magno, M.; Edwards-Murphy, F.; Pakrashi, V.; Popovici, E. An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors. Sensors 2016, 16, 448.
38. Aliyu, F.; Sheltami, T. Development of an energy-harvesting toxic and combustible gas sensor for oil and gas industries. Sens. Actuators B Chem. 2016, 231, 265-275.
39. Wu, F.; Rüdiger, C.; Yuce, M.R. Real-Time Performance of a Self-Powered Environmental IoT Sensor Network System. Sensors 2017, 16, 282.
40. Yick, J.; Mukherjee, B.; Ghosal, D. Wireless sensor network survey. Comput. Netw. 2008, 52, 2292-2330.
41. Bluetooth SIG, Inc. Introducing Bluetooth Mesh Networking. 2017. Available online: http://blog.bluetooth. com/introducing-bluetooth-mesh-networking (accessed on 20 April 2018).
42. Cypress Semiconductor Corporation. CYPRESS CYW43012. 2017. Available online: http://www.cypress. com/file/384986/download (accessed on 20 April 2018).
43. Texas Instruments. WiLinkTM8 Wi-FiR + BluetoothR/BLE Modules. 2016. Available online: http://www.ti. com/lit/ml/swpb012b/swpb012b.pdf (accessed on 20 April 2018).
44. Ray, P.P.; Agarwal, S. Bluetooth 5 and Internet of Things: Potential and architecture. In Proceedings of the 2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), Paralakhemundi, India, 3-5 Octomber 2016; pp. 1461-1465.
45. Pau, G.; Collotta, M.; Maniscalco, V. Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things. Energies 2017, 10, 992.
46. Di Marco, P.; Skillermark, P.; Larmo, A.; Arvidson, P.; Chirikov, R. Performance Evaluation of the Data Transfer Modes in Bluetooth 5. IEEE Commun. Stand. Mag. 2017, 1, 2.
47. Cypress Semiconductor Corporation. CYBLE-022001-00 EZ-BLETM Creator Module; Technical Manual; Cypress Semiconductor Corporation: San Jose, CA, USA, 2018.
48. IXYS Corporation. IXOLARTM High Efficiency SolarBIT; Technical Manual; IXYS Corporation: Milpitas, CA, USA, 2010.
49. Texas Instruments. bq25504 Ultra Low-Power Boost Converter With Battery Management for Energy Harvester Applications; Technical Manual; Texas Instruments: Dallas, TX, USA, 2011.
50. Tsai, H.Y.; Chen, G.H.; Lee, H.C. Poster Abstract: Using Low-Cost, Non-Sensor-Equipped BLE Beacons to Track People’s Movements. In Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), Pittsburgh, PA, USA, 18-21 April 2017; pp. 291-292.
51. Jeon, K.E.; She, J.; Soonsawad, P.; Ng, P.C. BLE Beacons for Internet of Things Applications: Survey, Challenges, and Opportunities. IEEE Internet Things J. 2018, 5, 2.