End-to-end reliability analysis of an IoT based smart agriculture

Kamyod, Chayapol

doi:10.1109/icdamt.2018.8376535

Cited by 22 publications

(10 citation statements)

References 20 publications

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“…Reliability is a crucial foundation for designing data-driven services across smart farming ecosystems. The reliability of data-driven systems depends on effective processes, data, and technologies [70]. As a major requirement, reliability should be considered in all stages of smart farming, from data acquisition to data preparation and model building.…”

Section: Reliabilitymentioning

confidence: 99%

A Platform Approach to Smart Farm Information Processing

et al. 2022

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With the rapid growth of population and the increasing demand for food worldwide, improving productivity in farming procedures is essential. Smart farming is a concept that emphasizes the use of modern technologies such as the Internet of Things (IoT) and artificial intelligence (AI) to enhance productivity in farming practices. In a smart farming scenario, large amounts of data are collected from diverse sources such as wireless sensor networks, network-connected weather stations, monitoring cameras, and smartphones. These data are valuable resources to be used in data-driven services and decision support systems (DSS) in farming applications. However, one of the major challenges with these large amounts of agriculture data is their immense diversity in terms of format and meaning. Moreover, the different services and technologies in a smart farming ecosystem have limited capability to work together due to the lack of standardized practices for data and system integration. These issues create a significant challenge in cooperative service provision, data and technology integration, and data-sharing practices. To address these issues, in this paper, we propose the platform approach, a design approach intended to guide building effective, reliable, and robust smart farming systems. The proposed platform approach considers six requirements for seamless integration, processing, and use of farm data. These requirements in a smart farming platform include interoperability, reliability, scalability, real-time data processing, end-to-end security and privacy, and standardized regulations and policies. A smart farming platform that considers these requirements leads to increased productivity, profitability, and performance of connected smart farms. In this paper, we aim at introducing the platform approach concept for smart farming and reviewing the requirements for this approach.

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Section: Reliabilitymentioning

confidence: 99%

A Platform Approach to Smart Farm Information Processing

et al. 2022

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“…In [103] the authors proposed a gateway redundancy model which reduced the RTT (return trip time) as the performance metric and proposed methodology lowers the return time to 1% from 14% during fault conditions. In [104] the authors quantified some QoS metrics, like delay throughput, and packet loss. In [105] the authors proposed a general model for a QoS-aware IoT infrastructure, that only deals with latency and bandwidth.…”

Section: B Communication Layermentioning

confidence: 99%

Reliable and Resilient AI and IoT-Based Personalised Healthcare Services: A Survey

Taimoor

Rehman

2022

IEEE Access

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Recent technological (e.g., IoT, 5G), and economic (e.g., UN 2030 Sustainable Development Goals) developments have transformed the healthcare sector towards more personalized and IoT-based healthcare services. These services are realized through control and monitoring applications that are typically developed using artificial intelligence (AI)/machine learning (ML) based algorithms, that play a significant role to highlight the efficiency of traditional healthcare systems. Current personalized healthcare services are dedicated in a specific environment to support technological personalization (e.g., personalized gadgets/devices). However, they are unable to consider different inter-related health conditions, leading to inappropriate diagnosis and affect sustainability and the long-term health/life of patients. Towards this problem, the state-of-the-art Healthcare 5.0 technology has evolved that supersede previous healthcare technologies. The goal of healthcare 5.0 is to achieve a fully autonomous healthcare service, that takes into account the interdependent effect of different health conditions of a patient. This paper conducts a comprehensive survey on personalized healthcare services. In particular, we first present an overview of key requirements of comprehensive personalized healthcare services (CPHS) in modern healthcare Internet of Things (HIoT), including the definition of personalization and an example use case scenario as a representative for modern HIoT. Second, we explored a fundamental three-layer architecture for IoTbased healthcare systems using both AI and non-AI-based approaches, considering key requirements for CPHS followed by their strengths and weaknesses in the frame of personalized healthcare services. Third, we highlighted different security threats against each layer of IoT architecture along with the possible AI and non-AI-based solutions. Finally, we propose a methodology to develop reliable, resilient, and personalized healthcare services that address the identified weaknesses of existing approaches.

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“…As a matter of fact, only a few papers deal with this concern. Kamyod [29] analyses and compares two main IoT communication architectures for small and medium-sized farms and evaluates the end-to-end reliability. In [30] a methodology based on the automatically generated fault tree is proposed to evaluate the reliability and availability of Wireless Sensor Networks in case of permanent failures.…”

Section: Classification Of Previous Workmentioning

confidence: 99%

Reliability Analysis of Wireless Sensor Network for Smart Farming Applications

Catelani

Ciani

Bartolini

et al. 2021

Sensors

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Wireless Sensor Networks are subjected to some design constraints (e.g., processing capability, storage memory, energy consumption, fixed deployment, etc.) and to outdoor harsh conditions that deeply affect the network reliability. The aim of this work is to provide a deeper understanding about the way redundancy and node deployment affect the network reliability. In more detail, the paper analyzes the design and implementation of a wireless sensor network for low-power and low-cost applications and calculates its reliability considering the real environmental conditions and the real arrangement of the nodes deployed in the field. The reliability of the system has been evaluated by looking for both hardware failures and communication errors. A reliability prediction based on different handbooks has been carried out to estimate the failure rate of the nodes self-designed and self-developed to be used under harsh environments. Then, using the Fault Tree Analysis the real deployment of the nodes is taken into account considering the Wi-Fi coverage area and the possible communication link between nearby nodes. The findings show how different node arrangements provide significantly different reliability. The positioning is therefore essential in order to obtain maximum performance from a Wireless sensor network.

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End-to-end reliability analysis of an IoT based smart agriculture

Cited by 22 publications

References 20 publications

A Platform Approach to Smart Farm Information Processing

A Platform Approach to Smart Farm Information Processing

Reliable and Resilient AI and IoT-Based Personalised Healthcare Services: A Survey

Reliability Analysis of Wireless Sensor Network for Smart Farming Applications

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