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The impact of IoT introduction across the board has been well reported. We thought we’d delve into another of the top verticals in IoT; transport and logistics.  

The benefits and growing need for transport monitoring is cropping up more and more; with more people comes more demand for both logistics and public transport. With an ever-expanding coverage network, there has never been a better time to get transport systems connected. It’s also quite a well-known fact that in general, transport systems across the world are not as effective as they should be (and very well could be).  

The word ‘transport’ covers both logistics, asset management and public transport. To make life a little easier, this blog post has been divided into two separate pieces; logistics and public transport.  

IoT in Logistics

A large reason behind why IoT is being introduced so rapidly in the logistics supply chain is that it creates an almost instantaneous impact; the elements of the supply chain become immediately visible. As Deloitte writes, ‘many companies across industries are feeling the pressure of rising customer expectations for speed, customisation and more.’ By monitoring the supply chain, C-suite and managers can react far faster to any changes in demand. This is backed up by the fact that in 2018, only 6% of organisations had full visibility into their supply chain and 65% had poor or no visibility beyond their tier-1 suppliers. (Tier-1 being companies that companies that supply parts or systems directly to OEMs).  

By making the supply chain visible, it also becomes agile. Companies can react and respond to fluctuations in demand whilst complying to regulatory standards – a win-win situation.  


However, it must be said that it isn’t as simple as connecting a few sensors. Logistics teams have to create entire ecosystems that continually exchange information, which means that the more silo-like the business practice is around installing IoT sensors, the trickier it can be to move to a more holistic, integrated one.  Interestingly, IoT is increasingly becoming paired with other digital technologies such as predictive analytics and artificial intelligence. Ultimately, by integrating with other digital systems transport and logistics carriers have an opportunity to reach a far more advanced stage of digital capability.  

What is vital to the increased uptake of IoT is that it provides both increased visibility and lower latency, both of which are ‘becoming table stakes for carriers and others in the logistics space.’  

Applications beyond the connected vehicle (from Deloitte):  

  • Predictive maintenance: when IoT joins with safety and maintenance plans, it can enable transportation providers to manage asset maintenance holistically. For example, sensors can gather data on things such as weather conditions and equipment stress in real-time.  When combined with AI and predictive analytics, this can then enhance predictive maintenance capabilities to predict impending failures. The hope is that this will then allow for fixes to be enabled whilst the asset is being used, which is expected to reduce fleet maintenance costs by up to 8% 


  • Transportation safety: Accidents and injuries are some of the transportation industry’s most visible issues. They also come with a large amount of risk for the parties involved. There have been a number of advancements around safety for both the driver and the public: in-vehicle telematics solutions use accelerometers, engine monitors and trackers to gather information on things such as braking data, fuel consumption, location and speed. Connected devices, such as mobile phones, then provide feedback to drivers and others if safely thresholds are breached. Another benefit being that IoT telematics solutions are expected to reduce both fuel consumption and the cost of incidents and insurance.  


  • Fleet monitoring and routing: By allowing all endpoints to communicate with each other in real time, an IoT ecosystem allows for the transportation provider to establish a dynamic network that accounts for demand and fleet availability and make real-time decisions regarding fleet routing and management. A well-known example of this is SmarTrucking, which is DHL’s fleet management solution. It uses sensor-enabled trucks to gather fleet data such as weather, traffic, shipment information and location, and combine these with telematics to transmit data to a centralised control tower. The control tower then uses predictive analysis, intelligent data science and onboard diagnostics to make real-time decisions on dynamic routing and fleet allocation.  


  • Terminal Operations: With the help of IoT and location tracking technology, for example GPS, trucking stations (terminals) can receive updated information on inbound shipments. This can include information such as storage requirements, shipment quantity and expected time of docking. As referred to earlier, by combining IoT with AI and predictive analytics, this data can then be used to better plan outbound shipments and manage capacity.  


  • Product life management (cold chain): Moving sensitive products, such as pharmaceuticals or temperature-sensitive products) through the supply chain has traditionally carried a high risk of losses. These losses are compounded by the challenge of measuring them during transportation whilst also complying with stringent safety requirements. Sensors that enable real-time temperature and humidity monitoring allows companies to monitor and distribute products more safely and efficiently, whilst also lowering loss-based costs.