Combined use of lifecycle management and IoT in smart cities

Hefnawy, Ahmed; Elhariri, Taha; Cherifi, Chantal; Robert, Jérémy; Bouras, Abdelaziz; Kubler, Sylvain; Främling, Kary

doi:10.1109/skima.2017.8294112

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…Although the model was developed with the data from EVs, it can be applied to the lithium-ion batteries that do not meet any longer the requirements of an EV application. It can still be used for the less-demanding grid-connected energy storage applications such as the battery energy storage system (BESS) for the sustainable energy management [68].…”

Section: Discussionmentioning

confidence: 99%

Comparing seven methods for state-of-health time series prediction for the lithium-ion battery packs of forklifts

Huotari,

Arora,

Malhi

et al. 2021

Preprint

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A key aspect for the forklifts is the state-of-health (SoH) assessment to ensure the safety and the reliability of uninterrupted power source. Forecasting the battery SoH well is imperative to enable preventive maintenance and hence to reduce the costs. This paper demonstrates the capabilities of gradient boosting regression for predicting the SoH timeseries under circumstances when there is little prior information available about the batteries. We compared the gradient boosting method with light gradient boosting, extra trees, extreme gradient boosting, random forests, long short-term memory networks and with combined convolutional neural network and long short-term memory networks methods. We used multiple predictors and lagged target signal decomposition results as additional predictors and compared the yielded prediction results with different sets of predictors for each method. For this work, we are in possession of a unique data set of 45 lithium-ion battery packs with large variation in the data. The best model that we derived was validated by a novel walk-forward algorithm that also calculates point-wise confidence intervals for the predictions; we yielded reasonable predictions and confidence intervals for the predictions. Furthermore, we verified this model against five other lithium-ion battery packs; the best model generalised to greater extent to this set of battery packs. The results about the final model suggest that we were able to enhance the results in respect to previously developed models. Moreover, we further validated the model for extracting cycle counts presented in our previous work with data from new forklifts; their battery packs completed around 3000 cycles in a 10-year service period, which corresponds to the cycle life for commercial Nickel-Cobalt-Manganese (NMC) cells.

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Section: Discussionmentioning

confidence: 99%

Comparing seven methods for state-of-health time series prediction for the lithium-ion battery packs of forklifts

Huotari,

Arora,

Malhi

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Hence, lifecycle management is important to manage business processes and data associated with heterogeneous connected objects in the smart city context [3]. For a smart city, lifecycle management is particularly important due to the following reasons [7][8]:…”

Section: Introductionmentioning

confidence: 99%

Does End of Life Matter in Smart Cities?

Hefnawy

Bouras

Cherifi

2018

Product Lifecycle Management to Support Industry 4.0

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In the smart city ecosystem, smart systems go through different phases of development from conception and design, through deployment and operation till end of service and retirement. Normally, city operators pay less attention to End of Life activities, compared to other phases of lifecycle. however, in the End of Life, the decommission of certain smart system shall be subject to applicable laws and regulations, like data privacy and cyber security. In addition, the outage of such smart system should be strategically aligned with the vision of the smart city. In this paper, we present the scenario of FIFA World Cup™ 2022, where Qatar has committed to donate part of its sports infrastructure to other countries. We particularly focus on the lifecycle of an IoT-enabled smart parking use-case in Lusail City.

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Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture

Lezoche

Hernández

Ruiz

et al. 2020

Computers in Industry

560

339

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income.pdf 4.0 should help meeting sustainable challenges by increasing the agri-food supply chain stakeholders revenues as well as decreasing their pressure for handling complex and external factors they cannot control, such as weather, market behaviours and policies, but also to react on time by visualising current trends in needs. This paper focus principally on the factory farm model issued from the European and north American style. In those typologies of farms the Industry 4.0 elements can be introduced and merged with the agricultural domain to create the Agri-Food 4.0. The focus is more specialised on the industrial farming although the Agri-Food 4.0 is started to be adapted also to the organic and silvo-pasture paradigms. Thus, this paper, considering a review over than two hundred papers, provides a contribution to knowledge by establishing the linkages between new 4.0 trends in technologies and Agri-Food Supply Chain Challenges, which opens the 4.0 research field for a multidisciplinary work. The choice of the literature review methodology focused firstly on key words related to the Agri-food technology, then the second approach was to focus on selected journals and at the end we looked for the data-based repository and the linked publications. To accomplish this, the structure in this paper is as follows: in the first place, a compressive state of the art of Agri-Food 4.0 related technologies is covered. In the second place, a review and contribution coming from digital technologies to the new supply chain methods in Agri-Food shows linkages with next trends and technologies. Next, and linked to the agri-food supply chain challenges, the fourth section presents new trends and models in agri-food supply chains, especially in the domain of risk management, collaboration, governance, cold chain management, globalization, information and communication technologies, Logistics, supply chain structures and sustainable agri-food supply chains. Finally, the fifth section covers the main conclusions, visions and perspectives for this novel research. 2-Agri-food 4.0 and Technologies a State of the Art The agricultural sector has been active in digital innovation for decades already. Especially the advances in Precision Agriculture, remote sensing, robots, farm management information

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Combined use of lifecycle management and IoT in smart cities

Cited by 3 publications

References 15 publications

Comparing seven methods for state-of-health time series prediction for the lithium-ion battery packs of forklifts

Comparing seven methods for state-of-health time series prediction for the lithium-ion battery packs of forklifts

Does End of Life Matter in Smart Cities?

Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture

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