Global cellular IoT connections to grow by three billion by 2028
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Tags: security, increase, federated learning, challenges, opportunities, cellular iot devices, data fraud, adoption, decentralized data approach, juniper research, machine learning models, transition, 2028, efficient automation, global, data management, data breaches, data security, 6.5 billion, industries, iot connectivity, iot networks, intelligent infrastructure management
Tags2: global, data breaches, data management, security, federated learning, intelligent infrastructure management, cellular iot devices, challenges, data security, increase, opportunities, data fraud, adoption, decentralized data approach, juniper research, machine learning models, transition, 2028, efficient automation, 6.5 billion, industries, iot connectivity, iot networks
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Part 1: The Growing Number of Cellular IoT Devices
A recent study by Juniper Research has revealed that the global number of cellular internet of things (IoT) devices is set to increase significantly in the coming years. By 2028, it is projected that there will be 6.5 billion cellular IoT devices, up from 3.4 billion in 2024. This surge in connections, estimated to be as much as 90%, presents both opportunities and challenges for the industry.
Part 2: The Need for Efficient Automation and Security
With this exponential growth in cellular IoT devices, managing the increasing volume of data and ensuring its security becomes crucial. Juniper Research highlights the importance of deploying new services that enable efficient automation of IoT device management and security. One such solution is federated learning, which allows operators to minimize security risks. Additionally, intelligent infrastructure management solutions are identified as key in handling the large increase in cellular data.
Part 3: The Transition to Federated Learning and the Future of IoT
The study also emphasizes the need for a transition from traditional machine learning models to federated learning models. Currently, machine learning models rely on data stored in a single location, making it easier for fraudulent players to exploit. Federated learning, on the other hand, leverages a decentralized data approach, reducing the chances of data fraud over IoT networks. By limiting the exposure of sensitive IoT data, federated machine learning helps mitigate the threat of data breaches.
As the cellular IoT market continues to grow, the security of data in transition and on devices becomes paramount. Failure to prioritize data security may deter industries with sensitive data from adopting a cellular IoT-based approach. It is crucial for platforms and operators to ensure the secure handling of data to maintain trust and drive the adoption of IoT connectivity.
Original page content A study by telecoms specialist Juniper Research has found the global number of cellular internet of things (IoT) devices will increase from 3.4 billion in 2024 to 6.5 billion by 2028. Yet despite the surge in connections, set to be as much as 90% in the timeframe, the analyst warned that managing this growth and cashing in on it would require the deployment of new services to enable the efficient automation of IoT device management and security, with federated learning in particular enabling operators to minimise security risks. The report, Global cellular IoT market 2024-2028, also identified intelligent infrastructure management solutions – which enable IoT users to automate the configuration of devices, security processes and connectivity in real time – as key to handling the large increase in cellular data. The research firm anticipates that global cellular IoT data generated will grow to 46PB (petabytes) in 2028, up from 21PB projected for the end of 2024. This is likely to lead to further investment in IoT automation services. The analyst noted that, at present, the majority of machine learning models are trained via data sources stored in a single location, making opportunities for fraudulent players a simpler task. In response, the study recommends that operators transition to federated learning models, a subset of machine learning that leverages a decentralised data approach to minimise the chances of data fraud over IoT networks. Juniper believes federated machine learning limits the exposure of sensitive IoT data, thus reducing the threat of data breaches. “As the number of cellular IoT connections grows, it is imperative that both platforms and operators ensure data is secure in transition and on device,” remarked research author Alex Webb. “A failure to do so will dissuade IoT users in industries with sensitive data from using a cellular IoT-based approach to connectivity.” “As the number of cellular IoT connections grows, it is imperative that both platforms and operators ensure data is secure in transition and on device” Alex Webb, Juniper Networks Similar research from international communications enabler BICS revealed a 156% year-on-year spike in the number of non-standalone 5G roamers for consumer and IoT devices across its network. BICS found that even though IoT is still in its adolescence, the increase in machine roamers using a 5G connection is an encouraging sign the industry is at long last picking up pace. A further study it cited, from Kaleido Intelligence, estimated non-standalone 5G roamers will exceed 100 million in 2024, and that overall consumer and IoT roaming data usage will rise by 36% to a total of 5,000PB. The BICS data also showed a much starker 277% rise in the number of IoT devices roaming on 5G connections. Even the variety of types of 5G devices is growing – up by 47% year on year in 2023. Read more about IoT BT launches smart city NB-IoT offer: UK’s leading comms provider launches multi-million-pound narrowband internet of things network to pave way for more smart cities and industries, creating cost-efficiency gains and costs savings for public sector. Wi-Fi HaLow begins real-world commercial IoT deployments: New Wi-Fi standard to address wide range of IoT applications and offer support for use cases including smart home, smart city, building automation, smart retail, industrial IoT and agriculture technology. BICS, Skylo unite to deliver GEO satellite NB-IoT connectivity: Connectivity enabler announces partnership with non-terrestrial network operator to deliver ubiquitous satellite-based narrowband internet of things connectivity for enterprises, letting IoT devices travel outside of their home country. Skylo, FocusPoint claim first for satellite-based IoT monitoring, escalation services: Non-terrestrial networks provider extends partnership with internet of things tech firm to link up its NTN satellite network for what it calls the first satellite-based IoT monitoring and escalation service. | Federated learning to automate platform management, configuration of devices, security processes and connectivity in real time will be key to handling large increase in data as telco network-based internet of things flourishes