Towards a traceability system based on cloud and fog computing

Mededjel, Mansour; Belalem, Ghalem; Neki, Abdelkader

doi:10.3233/mgs-170261

Cited by 19 publications

(12 citation statements)

References 16 publications

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“…Thus, raising the reliability in the marketed products. Mededjel et al (2017) proposed a system of food trackability based in IoT, cloud and hybrid cloud technologies, gathering information and registering events related to products in every place in the supply chain. The system accords to many requirements of trackability, like automatic identification, distributed/centered storage and data sharing, scalability support, heterogeneity, and answers in real time.…”

Section: Application Of Technologies In the Industrymentioning

confidence: 99%

“…(Gupta & Rakesh, 2018) The study did not determine which sensors should be used in view of the fact that it is based on a proposal for future application. (Mededjel et al 2017) The Radio Frequency Identification (RFID) sensors were applied in the study to monitor the quantity of products stored in a refrigerator. (Floarea & Sgârciu, 2016) Source: Authors (2021).…”

Section: (Paladino Et Al 2019)mentioning

confidence: 99%

“…(Gupta & Rakesh,, 2018) Automatic identification, distributed/centralized storage and data sharing, with support for scalability, heterogeneity and real-time responses. (Mededjel et al, 2017) Application of approaches that allow embedded devices to become more intelligent, reliable and autonomous. (Floarea & Sgârciu, 2016) Source: Authors (2021).…”

Section: Rq06 -What Are the Industry Gains With The Application Of The Proposal Of Each Study? Referencementioning

confidence: 99%

“…The challenge is to allow the implementation in large scale of devices to monitor the food, reduce frauds and use of pesticides in a way of approaching the business to the customer. Mededjel et al (2017) sign that heterogeneity of the technologies, with frequency, limits the tasks that are mandatory for the connection and functionality in the tracking chain. Floarea & Sgârciu, (2016) focus on the necessity of using a smart RFID package for the operation of its system control and, to find technological alternatives that allow the propagation of the waves within liquids or metals.…”

Section: Main Limitations and Challengesmentioning

confidence: 99%

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IoT and Raspberry Pi application in the food industry: a systematic review

Endres

Pelisser

Finco

et al. 2022

RSD

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The Industry 4.0 technologies are in ascension in the worldwide market, in Brazil still needs to be explored. It was made a Systematic Review to measure the application of IoT in the food industry. Some platforms were used to select works, applying the string “IoT AND Raspberry Pi AND Cheese”. It was possible to evidence the majority of IoT applications in the food industry, focus on the control of temperature, humidity, color, traceability of productive chain, and enlargement of sustainability in the food industry. The most difficulties faced in the conventional application of IoT are related to the high cost of proprietary arquitectures, qualified manpower and obstacles of data security implementation. There are alternatives that aim to reduce the costs of implementation, like the utilization of Raspberry Pi. The food industry presents potential application of technologies that aim for the quality of products, being an excellent opportunity.

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Section: Application Of Technologies In the Industrymentioning

confidence: 99%

Section: (Paladino Et Al 2019)mentioning

confidence: 99%

Section: Rq06 -What Are the Industry Gains With The Application Of The Proposal Of Each Study? Referencementioning

confidence: 99%

Section: Main Limitations and Challengesmentioning

confidence: 99%

See 2 more Smart Citations

IoT and Raspberry Pi application in the food industry: a systematic review

Endres

Pelisser

Finco

et al. 2022

RSD

View full text Add to dashboard Cite

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“…In addition, the input data for data scheduling in the Internet of Things system usually has the same size as a Distributed File System (HDFS) data block. During the submission process of the job, the schedulers creates a Task queue, and establish task-to-data block mapping for each data schedule in the queue [20]- [24]. For a multi-copy storage strategy, the same data schedule may appear in multiple task queues.…”

Section: Introductionmentioning

confidence: 99%

Sensing Cloud Computing in Internet of Things: A Novel Data Scheduling Optimization Algorithm

Sun

et al. 2020

IEEE Access

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In order to addressing the issues of data matching deviation and load imbalance during the data scheduling process of the Internet of Things, Sensing Cloud Computing in IoT: A Novel Data Scheduling Optimization (SCC-DSO) Algorithm is proposed in this paper. First, according to the processing capacity of the IoT working node, a data placement algorithm is designed to reasonably place the input data of the job. Second, the data scheduling queue is optimized based on the data block storage location information to reduce non-local execution of data scheduling. Furthermore, a data prefetching method is designed to pull the data required for non-local data scheduling in advance, and shorten the waiting time of the task for input data. Finally, simulation experiment evaluated by the task localization execution rate and response time is performed. The effectiveness and stability of the algorithm is verified compared with other algorithms. INDEX TERMS Sensing-cloud computing, Internet of Things, data scheduling, optimization algorithm.

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