Explore the full briefing

What is the Internet of Things?

What is an IoT platform?

What are the economic, sectoral and geographical impacts of IoT technology?

Are there vulnerabilities in the technology?

What are the key operational issues?

What are the key legal considerations?

What are the issues to consider in acquiring IoT technology?

What should manufacturers and suppliers of IoT technology be doing now?

What will the future of IoT technology look like?

What will the impact be on specific industries?

Energy

Oil and gas: IoT technology is already being deployed in the oil and gas industry as a means to improve operational efficiency.  Examples include the use of IoT-enabled sensors to analyse surface and subterranean environments, helping to optimise exploration efforts,[1] and remote monitoring of equipment, reducing the need for manual inspections.

Smart energy grids: IoT devices, in combination with AI, self-regulating systems and self-optimising systems, will enable production and consumption peaks to be smoothed out across clusters of energy generation units (for example, windfarms, solar energy, fuel cells), consumption units (for example, homes, and commercial and industrial users), storage units (for example, batteries, pumped-storage hydro-electric stations)[2] and demand side response services.  As well as facilitating system balancing, this will enable virtual power plants and enhance forecasting capabilities, improving energy security and reducing system costs.

Smart metering: smart meters will play an important role in the emergence of smart grids. A smart meter consists of hardware that includes real-time or near real-time IoT sensors, enabling two-way communication between the meter and the central system, permitting data to be gathered for remote reporting.  For example, under UK supply licence terms, with some exceptions, suppliers can access monthly, daily, or half-hourly energy consumption data, with stricter restrictions around usage and customer consent depending on the granularity of the data.

Electric vehicles (EVs) and autonomous vehicles (AVs): a smart electricity grid will be important for the integration of EVs into the network. In the future, IoT devices are expected to enable charging infrastructure to have a bi-directional grid connection (vehicle-to-grid), meaning that EVs act as battery storage, discharging electricity to balance the grid during peak times.[3]  IoT technology also allows AVs to be connected to one another, to traffic management systems and to vehicle manufacturers, aiding the creation of fully capable, self-driving autonomous vehicles.[4]  For more information on EVs and AVs, see our microsite, Autonomous Vehicles.

Financial Institutions

Credit assessments: in some jurisdictions lenders are beginning to experiment with including IoT sensor data about individuals in credit assessments.[5]  Moreover, for purposes of a mortgage application and underwriting, it is possible that lenders might able to better understand a home’s condition (and therefore its valuation) using IoT data collected about the property during its prior occupation.  Similarly, banks might benefit from IoT data that covers activities undertaken in, and condition of, retail industrial and agricultural businesses in making lending decisions.[6]

Consumer: lenders might in the future partner with white goods manufacturers to make credit offers to an individual if, say, IoT sensors in their washing machine began to show a risk of failure. An IoT network of ATMs, card-readers, and other point-of-sale devices can be used to assess a borrower’s expenditure and income for determining their ability and intent to repay, and further expenditure by defaulters can be curbed until repayment.

Trade finance: IoT sensors attached to goods in transit could be used as part of an automated trade finance platform, better matching flows of payments and goods between seller, buyer and bank in terms of trade receivables financing.

Personal investment management: a better understanding, based on IoT data, of an individual’s interests and inferences drawn about their attitude to risk could help personalise an investment management strategy for an individual.

Insurance:

  • IoT data is being used to personalise insurance risk (and therefore price), resulting in greater customer segmentation.  For example, IoT sensors in cars or mobile telephones can provide insurers with information on driving history and driver performance, and incentivise better driving behaviour. Similarly, telematics can be used to increase the accuracy of underwriting collision policies.[7] Home sensors (such as smart thermostats, alarms and cameras) provide insurers with a much more comprehensive understanding of household risks allowing underwriting decisions to be adjusted according to the data received.
  • Life insurance providers can use “fit-tech” devices to monitor the insured’s physical activity and reward positive lifestyle behaviours in terms of benefits or reduced premiums.
  • IoT data is being considered for commercial insurance products, including technology to assist underwriters with marine and cargo risks, as well as monitors within manufacturing that help assess risks for commercial liability policies.

Infrastructure, mining and commodities

Sustainable cities: IoT ecosystems will enable a huge range of initiatives supporting the development of sustainable cities, including smart bridges, smart waste collection, smart roads, connected ports and smart street lighting, all using IoT sensors and actuators to implement efficiencies and to gather data. For more information, see our client briefing, Future Ready: Sustainable Cities.

Infrastructure management: increasingly IoT solutions will be deployed to monitor and control the operation of infrastructure (like bridges, railway tracks, and windfarms) by sensing changes in structural conditions that might compromise safety or that otherwise require some form of intervention. IoT technology will also be used in scheduling maintenance activities. Using the technology in this way may improve incident management and emergency response coordination in relation to such infrastructure.  Data collected by IoT sensing devices can be analysed to determine the form of intervention required (from an emergency call-out to routine maintenance). It could also be used to co-ordinate supplier co-operation / involvement in the provision of services related to the particular infrastructure.

Mining:

  • There is already a vast amount of data collected on mine sites, such as drill hole data, blast hole data, data from machinery used, including trucks, shovels and plant, but the systematic collection of this data could be improved through IoT technology, and the resulting data sets analysed to drive efficiencies and drive up productivity.
  • IoT remote sensors attached to all key equipment operating on a mine could provide live feedback of this sampling data.  By feeding a continuous flow of data back into the mine model, it could be updated and refined daily or potentially even “live”.  Such a process could provide geologists with the information required to make on-the-day adjustments to the scheduling of the shovels, trucks and other equipment to ensure the head grade at the plant is optimised.  Employing advanced analytics, including cluster algorithms, on the data coming in could also help geologists understand where the initial mine model is being amended and potentially why.
  • IoT remote sensors could also be used to assay the product shipped from a mine, which would then be fed back into the mine model “live”.  Doing this could revolutionise the reconciliation process, potentially reducing the turnaround from months or even years to days or even hours.  It could therefore provide significant opportunities for mine operators to improve their mine model in a much shorter time frame (which, again, could drive up productivity).
  • Continuous environmental monitoring of an exploration or mine site could be achieved through the use of drone-mounted sensors connected into an IoT ecosystem.  They could be used to assist in environmental protection by monitoring air or water quality, atmospheric or soil conditions, and potentially even monitor the movements of wildlife and their habitats.  Such information could be fed back into a 3D model of the mine and its surrounding environment and could be used as a platform through which communications with shareholders, regulators or other interested stakeholders could be  undertaken, showing the mine development and how it is impacting upon the surrounding environment.  Deploying the technology in this way could significantly assist mining businesses in ensuring that they comply with their environmental obligations.  The mining business’s public relations strategy could also benefit from the use of IoT technology as it could use the information gathered to demonstrate clearly its commitment to social and environmental responsibility, while at the same time discouraging poor environmental practice. It simply reflects the fact that investors expect increasing transparency and ethical behaviour, and IoT technology could assist in meeting such expectations. 
  • For more information, see our client briefing, Disruptive Technologies in the Mining Industry.

Food and agribusiness:

  • IoT and related digital technologies  increasingly permeate the agribusiness sector. The use of technology to bring precision analysis to the business of agriculture – known as “precision agriculture” – enables farmers to make better decisions with greater flexibility across all aspects of farming, reducing costs and improving yields.  IoT technologies facilitate the collection of data, which is then analysed for use in decision-making or to generate (for example) real time adjustments of equipment and the creation of geo-spatial maps.
  • For more information in relation to food and agribusinesses and technology, see our Sustainable Agribusiness Hub.

Life sciences and healthcare

Remote patient monitoring devices: IoT technology is being deployed to enable monitoring of patients outside clinical settings. It may consist of IoT sensors that measure physiological parameters, an interface between the sensors and a centralised data repository or healthcare provider (including via IoT connectivity), and diagnostic application software that develops recommendations and alerts based on the analysis of collected data.  Physiological data (such as blood pressure, heart functioning, and glucose levels) are collected by IoT sensors on peripheral devices. Examples include blood pressure cuffs, pulse oximeters and glucometers.  The data are evaluated for problems by a healthcare professional or via a clinical support algorithm, and appropriate alerts are issued if a problem is detected. The data can also be used for long term diagnosis and monitoring of chronic conditions. Subject to privacy requirements, the data lends itself to big data analytics when collected as part of wider clinical trials.

Automation of drug delivery systems: using IoT sensors and actuators, medicine can be automatically administered to patients on an as-needed basis, using real-time patient health data.[8]

Technology and innovation

Security: as security and safety of IoT ecosystems becomes increasingly the subject of regulatory attention, specialist security vendors may benefit from expanding demand for bespoke IoT security solutions – both within IoT devices as well as on an end-to-end basis within an IoT ecosystem (including, for example, managed services for security infrastructure).

Integration: as described elsewhere (see What Will the Future of IoT Look Like?), an IoT ecosystem is typically made up of disparate component elements not supplied in accordance with the requirements of a single end-to-end specification.  This may lead to market demand for the role of systems integrator.

Standards: as described elsewhere (see What are the Key Operational Issues?), IoT ecosystems lack unifying technical standards, adversely impacting security and data exchange.  Technology vendors will want their own technical standards to prevail. It is possible that a vendor whose technical standard offers added value within an adaptable IoT solution may be able to gain significant market share.

Certification: regulators and particularly purchasers of Industrial Internet of Things solutions may increasingly look to mitigate security and safety risk inherent in lack of end-to-end IoT security compliance.  They may increasingly require certification of end-to-end security requirements, giving rise to opportunities for certification bodies and businesses.

Big data analytics: IoT ecosystems provide a vast amount of data, lending itself to big data analytics.  Businesses with big data analytics platforms will increasingly look to pair up with IoT platform providers, or themselves provide big data analytics in combination with their own IoT platforms.

Transport

Intelligent transport systems: IoT technology will increasingly support the development of intelligent transport systems. The technology will play a part in integrating communications, control, and information processing across transportation systems, including in relation to autonomous vehicles and infrastructure. Interaction between these components will enable communication with and between autonomous vehicles, smart traffic control, smart parking, toll collection, logistics and fleet management, and safety and road assistance. Such interactions will create vast data sets that can be used in big data analytics projects.  Data collected may include travel time and speed data for vehicles, emergency vehicle notifications (when an accident occurs), and autonomous vehicle-to-vehicle and vehicle-to-infrastructure data (and vice versa). These data can be used to detect rain (wiper activity) and congestion (frequent braking activities) and (in relation to big data analytics) to predict likely traffic flows and volumes at any given time and date. For more information, see our video Future Ready: Sustainable Cities.

Shipping: IoT sensors will not only help in the physical interactions between a vessel, port and other vessels, but also in relation to the goods they carry.  For example, IoT sensors could be used to confirm when shipping containers arrive at port, are unloaded and reach their destination.  In combination with distributed ledger technology, IoT data could be used to automate shipping documentation, such as bills of lading and documentary letters of credit.  IoT technology can also have benefits in ship maintenance and technical management, allowing repairs to be anticipated more accurately and for works to be scheduled more efficiently within a ship’s trading schedule.  For more information, see our client briefing, Autonomous Ships – What Needs to be Done to Make Them a Reality?

Aviation: IoT technology can be used to manage flight data, making suggestions to the pilot based on fuel efficiency and time savings, and also within an airline’s fleet and / or between airports to facilitate the better allocation of aircraft or gates, as applicable. It can give maintenance providers a fuller picture of the stresses that the part in front of them has encountered.  It can also assist with ticketing data, facilitating the rescheduling and rebooking of flights, and can be used in airport infrastructure, improving and tracking the passenger experience from check-in of luggage through passport control to boarding.  For more information.

Rail: as well as being employed in safety systems, IoT sensors can monitor the condition of track as well as tracking the lifecycle and maintenance of rolling stock, thereby permitting repairs to be carried out quickly and enabling routine maintenance to be scheduled efficiently.  IoT  technology can also be used to monitor passenger occupancy levels, to predict demand for extra services, as well as facilitating end-to end shipment tracking across rail freight system and interaction with customs and other agencies.

 

 

[1] https://enterpriseiotinsights.com/20160909/internet-of-things/upstream-oil-and-gas-tag31-tag99

[2] European Commission, Cross-Cutting Business Models for IoT, 2017, page 24.

[3] https://www.engerati.com/transmission-and-distribution/article/communications-networks-technologies/communication

[4] https://www.iotevolutionworld.com/autonomous-vehicles/articles/440238-implementation-the-iot-transportation-autonomous-vehicles.htm

[5] Scott R Peppet, Regulating the Internet of Things: First Steps Towards Managing Discrimination, Privacy, Security, and Consent 93 Tex. L. Rev 85 2014 – 2015, page 123.

[6] Jim Eckenrode, The Derivative Effect: How Financial Services can Make IoT technology Pay Off, Deloitte, https://www2.deloitte.com/insights/us/en/focus/internet-of-things/iot-in-financial-services-industry.html?id=us:2el:3dc:dup1166:eng:fsi:iot:dcpromo, 13 October 2015.

[7] Jim Eckenrode, The Derivative Effect: How Financial Services can Make IoT technology Pay Off, Deloitte, https://www2.deloitte.com/insights/us/en/focus/internet-of-things/iot-in-financial-services-industry.html?id=us:2el:3dc:dup1166:eng:fsi:iot:dcpromo, 13 October 2015.

[8] European Commission, Cross-Cutting Business Models for IoT, 2017, page 55.