This paper explores the role of Internet of Things (IoT) and its impact on supply chain management (SCM) through an extensive literature review. Important aspects of IoT in SCM are covered including IoT definition, main IoT technology enablers and various SCM processes and applications. We offer several categorisation of the extant literature, such as based on methodology, industry sector and focus on a classification based on major supply chain processes. In addition, a bibliometric analysis of the literature is also presented. We find that most studies have focused on conceptualising the impact of IoT with limited analytical models and empirical studies. In addition, most studies have focused on the delivery supply chain process and the food and manufacturing supply chains. Areas of future SCM research that can support IoT implementation are also identified.

Internet of things and supply chain management: a literature review

Internet of Things (IoT) is reshaping the incumbent industry to smart industry featured with data-driven decision-making. However, intrinsic features of IoT result in a number of challenges, such as decentralization, poor interoperability, privacy, and security vulnerabilities. Blockchain technology brings the opportunities in addressing the challenges of IoT. In this paper, we investigate the integration of blockchain technology with IoT. We name such synthesis of blockchain and IoT as blockchain of things (BCoT). This paper presents an in-depth survey of BCoT and discusses the insights of this new paradigm. In particular, we first briefly introduce IoT and discuss the challenges of IoT. Then, we give an overview of blockchain technology. We next concentrate on introducing the convergence of blockchain and IoT and presenting the proposal of BCoT architecture. We further discuss the issues about using blockchain for fifth generation beyond in IoT as well as industrial applications of BCoT. Finally, we outline the open research directions in this promising area.

Blockchain for Internet of Things: A Survey

http://www.cs.hut.fi/~framling/Publications/intelligentproducts_final.pdf

Intelligent Products: A survey

Auto ID systems and intelligent manufacturing control

Integration of renewable energy and optimization of energy use are key enablers of sustainable energy transitions and mitigating climate change. Modern technologies such the Internet of Things (IoT) offer a wide number of applications in the energy sector, i.e, in energy supply, transmission and distribution, and demand. IoT can be employed for improving energy efficiency, increasing the share of renewable energy, and reducing environmental impacts of the energy use. This paper reviews the existing literature on the application of IoT in in energy systems, in general, and in the context of smart grids particularly. Furthermore, we discuss enabling technologies of IoT, including cloud computing and different platforms for data analysis. Furthermore, we review challenges of deploying IoT in the energy sector, including privacy and security, with some solutions to these challenges such as blockchain technology. This survey provides energy policy-makers, energy economists, and managers with an overview of the role of IoT in optimization of energy systems.

Internet of Things (IoT) and the Energy Sector

In this paper, we present academic research activities and industrial technology transfer conducted at CRAN-CNRS UMR 7039 Laboratory concerning on one hand high level services environment definition based on low cost RFID Tagged product for smart product concept achievement in an ambient service architecture based on standard IP technologies, and on a second hand RFID deployment in wood industry for logistic and product driven factory management.

https://hal.archives-ouvertes.fr/hal-00140295/document

Ambient RFID Services Infrastructure & RFID Deployment in Wood industry

This paper presents a research work which considers programmable Escort Memories systems like parts of a global distributed database system providing manufacturing control, traceability, quality and maintenance assistance,...

/pdf/individual-product-data-management-for-fms-control-a-step-to-4b44znj2q1.pdf

Individual Product Data Management for FMS Control: a Step to Mobile DataBase Nodes Integration

Neighbour discovery is crucial for mobile ad-hoc networks and especially in Internet of Things (IoT) networks which are distributed by nature and built on mobile, communicating, and mostly battery-powered autonomous IoT devices. The challenge of efficient neighbour discovery in such architecture is to achieve both low latency and high energy efficiency discovery process, which have been shown to be major issues in the scientific community. In this paper, we contribute to the resolution of this problem applied on Bluetooth Low Energy (BLE) personal area network. A new neighbour discovery protocol called Snowball is proposed, which leverages the advertising and scanning features of BLE beaconing mode. Snowball provides new delay parameters upon the BLE stack to achieve a stable duty cycle schedule in the neighbourhood, which guarantee an efficient and low energy discovery process. The performance of Snowball is discussed and evaluated by simulation using Netlogo, and also by a practical experimentation using ESP32-based IoT devices.

Snowball: An Asynchronous Probabilistic Protocol for Neighbour Discovery in Mobile BLE Network

A flexible manufacturing cell with integrated quality control is being developed by the LACN. Dimensional control is realized on a coordinate measuring machine. Integrated inspection allows an appropriate feedback on the manufacturing process with the following benefits: 


measurement analysis ensures on-line corrections of N.C. machine tool programs. Thermal drift and tool wear are predicted during processing. For this purpose an auto-regressive model identifies dimensional fluctuations and then corrections values are estimated through a Kalman filter;


dimensional results allow storage by the cell robot according to quality classification.



Quality determination for part scheduling and automatic correction planning of N.C. programs are defined in the cell program.

In-process quality control and corrective feedback in a flexible manufacturing cell

Indoor positioning is nowadays an emerging and mandatory technology for Internet of Things. Various solutions have been proposed in the literature to achieve high localization accuracy. However, these existing solutions are cloud-based, thus, all the computing and intelligence is implemented in the Cloud. In this paper, we present a new positioning system which embedded all the computing in the mobile device. The proposed solution achieves lower energy consumption while still offering high accuracy of 1.5 meters within an industrial building area. To this end, BLE beacons, RSSI, and trilateration techniques are exploited. Moreover, mobile devices are controlled using MQTT protocol. All advantages of our contribution are presented using various real experiments in an industrial building.

Eddy Bajic

Papers

Ambient RFID Services Infrastructure & RFID Deployment in Wood industry

Individual Product Data Management for FMS Control: a Step to Mobile DataBase Nodes Integration

Snowball: An Asynchronous Probabilistic Protocol for Neighbour Discovery in Mobile BLE Network

In-process quality control and corrective feedback in a flexible manufacturing cell

Experimental Study of Embedded and Energy Efficient BLE Positioning System for Mobile IoT Devices