Corpus ID: 235422489

iThing: Designing Next-Generation Things with Battery Health Self-Monitoring Capabilities for Sustainable IoT in Smart Cities

  title={iThing: Designing Next-Generation Things with Battery Health Self-Monitoring Capabilities for Sustainable IoT in Smart Cities},
  author={Aparna Sinha and Debanjan Das and Venkanna Udutalapally and Mukil Kumar Selvarajan and S. Mohanty},
An accurate and reliable technique for predicting Remaining Useful Life (RUL) for battery cells proves helpful in battery-operated IoT devices, especially in remotely operated sensor nodes. Datadriven methods have proved to be the most effective methods until now. These IoT devices have low computational capabilities to save costs, but Data-Driven battery health techniques often require a comparatively large amount of computational power to predict SOH and RUL due to most methods being feature… Expand


Eternal-Thing: A Secure Aging-Aware Solar-Energy Harvester Thing for Sustainable IoT
A paradigm shift research that addresses a secure self-sustainable solar-energy harvesting system (EHS) with a security mechanism is proposed, which incorporates Physically Unclonable Functions for the security of EHS along with an aging sensor for recycled IC detection. Expand
Health Prognosis for Electric Vehicle Battery Packs: A Data-Driven Approach
A novel dual Gaussian process regression model is designed to predict SOH over the entire cycle life and RUL near the end of life of battery packs, showing the prospect of health prognosis using multiple health indicators in automotive applications. Expand
State-of-Health Estimation and Remaining-Useful-Life Prediction for Lithium-Ion Battery Using a Hybrid Data-Driven Method
A new hybrid ensemble data-driven method is proposed to accurately predict the state-of-health (SOH) and remaining-useful-life (RUL) of Li-ion batteries. Expand
A Review of Battery State of Health Estimation Methods: Hybrid Electric Vehicle Challenges
This study provides a review of the main battery SOH estimation methods, enlightening their main advantages and pointing out their limitations in terms of real time automotive compatibility and especially hybrid electric applications. Expand
Practical Issues of RF Energy Harvest and Data Transmission in Renewable Radio Energy Powered IoT
A new model is proposed to accurately describe the energy harvesting process and the power consumption for sustainable IoT devices and the experiment results show that the new model matches the performance ofustainable IoT devices very well in the real scenario. Expand
State-of-Health Estimation of Lithium-Ion Batteries Using Incremental Capacity Analysis Based on Voltage–Capacity Model
The proposed model-based method shows a high accuracy for battery SOH estimation and an expected robust performance against the initial aging status and practical cycling condition and is validated with experimental data from different battery chemistries. Expand
On Predicting the Battery Lifetime of IoT Devices: Experiences from the SPHERE Deployments
This paper contrasts real-world battery lifetimes and discharge patterns against battery lifetime predictions that were conducted during the development of the deployed system, and summarises key lessons learned that could potentially accelerate future IoT deployments of similar scale and nature. Expand
A remaining useful life prediction approach for lithium-ion batteries using Kalman filter and an improved particle filter
A novel PF-based method for RUL estimation of lithium-ion batteries is developed combining Kalman filter and particle swarm optimization (PSO), which demonstrates the higher accuracy of the proposed method. Expand
The Remaining Useful Life Prediction by Using Electrochemical Model in the Particle Filter Framework for Lithium-Ion Batteries
A new electrochemical-model-based particle filter (PF) framework for LIB RUL prediction is proposed and shows better accuracy and stability, which provides a choice for achieving high-quality Rul prediction. Expand
IOT based Electrical Device Surveillance and Control System
  • Alok Gupta, R. Johari
  • Computer Science
  • 2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU)
  • 2019
An energy saving electrical device Surveillance and Control system based on IOT and two different model approaches is followed depending on the nature of application. Expand