The Connected Future | IoT advancement and 5G Deployment challenges
Dr. Evangelo Damigos; PhD | Head of Digital Futures Research Desk
- Sustainable Growth and Tech Trends
Publication | Update: Oct 2020
The 5G benefits, like greater speeds and increased operational efficiencies, lead to more innovations. But 5G also creates new opportunities for hackers.
According to Liyuan Liu ‘Privacy and Security Issues in the 5G-Enabled Internet of Things’, Internet of Things (IoT) are changing the way we live and work. Their success and real value come from the establishment of services on top of the connected IoT devices. According to the Ericsson Mobility Report, there will be over 30 billion connected devices worldwide by 2023, of which around 20 billion will be IoT related devices. Between 2017 and 2023, IoT devices are expected to increase at a CAGR (Compound Annual Growth Rate) of 19 percent, driven by promising IoT use cases, like smart wearables, smart display, smart metering, robotic control/production automation, robotic surgery, autonomous driving car, and drone surveillance. These applications are usually integrated with wireless mobile communications.
Currently, a number of smart IoT devices exploit cellular networks like 3G and 4G LTE to maintain their connectivity and their connection with the cloud data centers. As the skyrocketing of data produced by increasingly large number of IoT devices, there are several burning issues to be solved in the application environments. For example, the transmission latency and reliability of current cellular networks cannot be guaranteed, which in turn limits the effectiveness and feasibility of many emerging IoT applications, such as the autonomous driving car and robotic surgery which ask for ultra-low latency and ultra-high reliability. 5G has been introduced with the capability of high throughput, low latency, high reliability, and increased scalability to enable massive number of devices with best QoS and QoE provision of ubiquitous connectivity solution to fulfill diversified IoT application requirements. This brings potentials to deploy more connected devices without worrying about an overcrowded network exacerbating existing issues.
The high speed and reliable connectivity underpinned by 5G will create new possibilities for IoT services far beyond those available today.
In addition, the enabling technologies of 5G, including functions virtualization and software defined networking, massive MIMO (Multiple Input and Multiple Output), mobile/edge computing, and ultra-dense networks, have great potentials to usher in a new era of IoT, aiming to smoothly and flexibly support heterogeneous IoT services with distinct business characteristics under massive smart devices. Furthermore, IoT will bring a rich source of big data.
The powerful role of big data analytics in 5G can undoubtedly benefit IoT advancement.
According to Ericsson research, from a user perspective, 5G is inherently different to any of the previous mobile generations. Machine-type communication, enabled by 5G, is widely anticipated to become the strategic difference and unique selling point of 5G in the long run. 5G networks will serve as critical infrastructures to facilitate the digitization, automation and connectivity to machines, robots and transport solutions etc. Thus, there is significant value at stake and, so too, a significantly different tolerance for risk
Using IoT devices without a private 5G network or adequate technical knowledge could put organizations' and their employees' privacy at risk.
"You absolutely have to have [5G security] on your radar right now," said Monique Becenti, channel and product specialist at cybersecurity provider SiteLock. It's also critical to have security measures in place for personal data.
"If you're using a mobile device for banking transactions you're leaving that susceptible to an attacker intercepting that data,'' she said. "With 5G, our main concern is with IoT innovations."
Often, developers face pressure to get software quickly to market so critical testing could be missed, Becenti said. "With 5G this isn't any different--especially in a market where security may not be top of mind."
She pointed out that the IoT devices market isn't regulated and therefore not required to meet certain security requirements, despite cyberattacks like the Mirai botnet.
"Devices are open right now and susceptible … so there are more potential entry points for attackers" that are scanning for open ports in the devices' software so they can deploy malicious bots and scripts.
Ericsson contests that it is imperative that IoT devices are secure from the start to protect personal data, business-sensitive information, and critical infrastructure.
Objectives and Study Scope
This study has assimilated knowledge and insight from business and subject-matter experts, and from a broad spectrum of market initiatives. Building on this research, the objectives of this market research report is to provide actionable intelligence on opportunities alongside the market size of various segments, as well as fact-based information on key factors influencing the market- growth drivers, industry-specific challenges and other critical issues in terms of detailed analysis and impact.
The report in its entirety provides a comprehensive overview of the current global condition, as well as notable opportunities and challenges.
The analysis reflects market size, latest trends, growth drivers, threats, opportunities, as well as key market segments. The study addresses market dynamics in several geographic segments along with market analysis for the current market environment and future scenario over the forecast period.
The report also segments the market into various categories based on the product, end user, application, type, and region.
The report also studies various growth drivers and restraints impacting the market, plus a comprehensive market and vendor landscape in addition to a SWOT analysis of the key players. This analysis also examines the competitive landscape within each market. Market factors are assessed by examining barriers to entry and market opportunities. Strategies adopted by key players including recent developments, new product launches, merger and acquisitions, and other insightful updates are provided.
Research Process & Methodology
We leverage extensive primary research, our contact database, knowledge of companies and industry relationships, patent and academic journal searches, and Institutes and University associate links to frame a strong visibility in the markets and technologies we cover.
We draw on available data sources and methods to profile developments. We use computerised data mining methods and analytical techniques, including cluster and regression modelling, to identify patterns from publicly available online information on enterprise web sites.
Historical, qualitative and quantitative information is obtained principally from confidential and proprietary sources, professional network, annual reports, investor relationship presentations, and expert interviews, about key factors, such as recent trends in industry performance and identify factors underlying those trends - drivers, restraints, opportunities, and challenges influencing the growth of the market, for both, the supply and demand sides.
In addition to our own desk research, various secondary sources, such as Hoovers, Dun & Bradstreet, Bloomberg BusinessWeek, Statista, are referred to identify key players in the industry, supply chain and market size, percentage shares, splits, and breakdowns into segments and subsegments with respect to individual growth trends, prospects, and contribution to the total market.
Research Portfolio Sources:
Global Business Reviews, Research Papers, Commentary & Strategy Reports
M&A and Risk Management | Regulation
The future outlook “forecast” is based on a set of statistical methods such as regression analysis, industry specific drivers as well as analyst evaluations, as well as analysis of the trends that influence economic outcomes and business decision making.
The Global Economic Model is covering the political environment, the macroeconomic environment, market opportunities, policy towards free enterprise and competition, policy towards foreign investment, foreign trade and exchange controls, taxes, financing, the labour market and infrastructure. We aim update our market forecast to include the latest market developments and trends.
Review of independent forecasts for the main macroeconomic variables by the following organizations provide a holistic overview of the range of alternative opinions:
As a result, the reported forecasts derive from different forecasters and may not represent the view of any one forecaster over the whole of the forecast period. These projections provide an indication of what is, in our view most likely to happen, not what it will definitely happen.
Short- and medium-term forecasts are based on a “demand-side” forecasting framework, under the assumption that supply adjusts to meet demand either directly through changes in output or through the depletion of inventories.
Long-term projections rely on a supply-side framework, in which output is determined by the availability of labour and capital equipment and the growth in productivity.
Long-term growth prospects, are impacted by factors including the workforce capabilities, the openness of the economy to trade, the legal framework, fiscal policy, the degree of government regulation.
Direct contribution to GDP
The method for calculating the direct contribution of an industry to GDP, is to measure its ‘gross value added’ (GVA); that is, to calculate the difference between the industry’s total pretax revenue and its total boughtin costs (costs excluding wages and salaries).
Forecasts of GDP growth: GDP = CN+IN+GS+NEX
GDP growth estimates take into account:
All relevant markets are quantified utilizing revenue figures for the forecast period. The Compound Annual Growth Rate (CAGR) within each segment is used to measure growth and to extrapolate data when figures are not publicly available.
Our market segments reflect major categories and subcategories of the global market, followed by an analysis of statistical data covering national spending and international trade relations and patterns. Market values reflect revenues paid by the final customer / end user to vendors and service providers either directly or through distribution channels, excluding VAT. Local currencies are converted to USD using the yearly average exchange rates of local currencies to the USD for the respective year as provided by the IMF World Economic Outlook Database.
Industry Life Cycle Market Phase
Market phase is determined using factors in the Industry Life Cycle model. The adapted market phase definitions are as follows:
The Global Economic Model
The Global Economic Model brings together macroeconomic and sectoral forecasts for quantifying the key relationships.
The model is a hybrid statistical model that uses macroeconomic variables and inter-industry linkages to forecast sectoral output. The model is used to forecast not just output, but prices, wages, employment and investment. The principal variables driving the industry model are the components of final demand, which directly or indirectly determine the demand facing each industry. However, other macroeconomic assumptions — in particular exchange rates, as well as world commodity prices — also enter into the equation, as well as other industry specific factors that have been or are expected to impact.
Forecasts of GDP growth per capita based on these factors can then be combined with demographic projections to give forecasts for overall GDP growth.
Wherever possible, publicly available data from ofﬁcial sources are used for the latest available year. Qualitative indicators are normalised (on the basis of: Normalised x = (x - Min(x)) / (Max(x) - Min(x)) where Min(x) and Max(x) are, the lowest and highest values for any given indicator respectively) and then aggregated across categories to enable an overall comparison. The normalised value is then transformed into a positive number on a scale of 0 to 100. The weighting assigned to each indicator can be changed to reﬂect different assumptions about their relative importance.
The principal explanatory variable in each industry’s output equation is the Total Demand variable, encompassing exogenous macroeconomic assumptions, consumer spending and investment, and intermediate demand for goods and services by sectors of the economy for use as inputs in the production of their own goods and services.
Elasticity measures the response of one economic variable to a change in another economic variable, whether the good or service is demanded as an input into a final product or whether it is the final product, and provides insight into the proportional impact of different economic actions and policy decisions.
Demand elasticities measure the change in the quantity demanded of a particular good or service as a result of changes to other economic variables, such as its own price, the price of competing or complementary goods and services, income levels, taxes.
Demand elasticities can be influenced by several factors. Each of these factors, along with the specific characteristics of the product, will interact to determine its overall responsiveness of demand to changes in prices and incomes.
The individual characteristics of a good or service will have an impact, but there are also a number of general factors that will typically affect the sensitivity of demand, such as the availability of substitutes, whereby the elasticity is typically higher the greater the number of available substitutes, as consumers can easily switch between different products.
The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
Proportion of the budget consumed by the item. Products that consume a large portion of the consumer’s budget tend to have greater elasticity.
Elasticities tend to be greater over the long run because consumers have more time to adjust their behaviour.
Finally, if the product or service is an input into a final product then the price elasticity will depend on the price elasticity of the final product, its cost share in the production costs, and the availability of substitutes for that good or service.
Prices are also forecast using an input-output framework. Input costs have two components; labour costs are driven by wages, while intermediate costs are computed as an input-output weighted aggregate of input sectors’ prices. Employment is a function of output and real sectoral wages, that are forecast as a function of whole economy growth in wages. Investment is forecast as a function of output and aggregate level business investment.