Hodos Media Limited Public Funding

The "FleetfootAI for Driver Advancement" project, led by Hodos in collaboration with Specialist Vehicle Rental and Omnia Smart Technologies, represents a major step forward in driver training and fleet management within the UK logistics sector. Utilising the latest advancements in artificial intelligence and machine learning, the FAIDA project aims to significantly enhance driver skills and fleet performance, promoting safer and more efficient operations across the industry. Building on the insights gained from the successful AIPTO project, FAIDA seeks to address the critical gaps in traditional fleet management systems, which often focus primarily on vehicle tracking and overlook the essential aspect of driver behaviour. By enhancing our existing Fleetfoot platform with advanced AI and sophisticated CCTV telematics, FAIDA will provide a dynamic, data-driven training experience that actively engages drivers both before and after training sessions. The core of FAIDA is its innovative, data-led training package that seamlessly integrates AI analytics, video footage and practical, hands-on instruction. Before and after each training session, instructors will utilise the platform to review driving patterns and behaviours with students, supported by detailed video feedback. Each significant driving event captured during sessions is video-tagged and geographically mapped, allowing for comprehensive analysis. This feature enables instructors and drivers to collaboratively review and discuss driving incidents, facilitating a deeper understanding and improvement of eco-driving techniques. The real-time data collected through vehicle-mounted telematics, coupled with AI-triggered CCTV that monitors both the driver and the road, provides a resource for creating customised training modules. This approach not only enhances drivers' understanding of their own performance but also ensures that the skills learned are consistently applied, leading to tangible improvements in fleet safety and operational efficiency. FAIDA's collaboration includes Specialist Vehicle Rental, which provides access to a fleet of vehicles for several driver training organisations, and Omnia, which supplies the cutting-edge hardware and technological expertise necessary for the project. This partnership ensures that the FAIDA platform remains at the forefront of technological innovation, is deeply relevant to industry needs, and has a direct route to market through established channels. As an innovative solution to modern fleet management and driver training challenges, FAIDA stands to deliver significant advancements in safety, efficiency, and environmental responsibility within the logistics sector. This project is not just about enhancing the way we train drivers; it's about setting new standards for the integration of technology in transportation, paving the way for a safer and more sustainable future.

FleetMind is an ambitious project poised to redefine waste management for local councils in the UK. It tackles the pressing need for more efficient and responsive waste collection services, a challenge magnified by urban growth and changing waste patterns. Traditional collection methods, often rigid and outdated, fail to keep pace with the dynamic demands of modern communities, leading to inefficiencies that strain budgets, the environment, and public satisfaction. At the heart of FleetMind is a sophisticated Artificial Intelligence (AI) and Machine Learning (ML) framework designed to overhaul the control room operations of waste collection fleets. Rather than relying on static, inflexible systems, FleetMind will leverage real-time data to adapt and optimise waste collection routes and schedules continuously. This data includes a variety of inputs such as collection frequency, traffic conditions, vehicle capacities, and predictive waste generation models. The system's innovation centres on its ability to recalibrate in real-time, ensuring waste collection is both efficient and adaptable. The project is set to deliver a multitude of benefits: 1. **Cost Reduction:** By enhancing operational efficiency, FleetMind will generate significant savings for local councils. This financial relief could enable reinvestment into community services or potentially reduce waste collection costs for residents. 2. **Resource Optimisation:** With live data analysis, FleetMind will ensure better asset deployment, leading to improved service delivery, such as reduced missed collections and wider coverage. 3. **Environmental Benefits:** Optimised routes and schedules will curtail unnecessary vehicle movement, thereby decreasing emissions and contributing to cleaner air, in line with environmental sustainability goals. Initiating with Flintshire County Council and Cumberland Council, FleetMind aims to craft a new benchmark in waste management that marries cutting-edge technology with practical application. This collaboration, which includes expertise from Omnia, TRL, and Hodos, is a step towards a more efficient, eco-friendly, and cost-effective future for UK waste services.

The "AI Powered Telematics Optimisation Study" (AIPTO) is a pioneering project aimed at transforming the fleet management industry through the integration of artificial intelligence (AI) and machine learning (ML) technologies. This project will significantly enhance the capabilities of Fleetfoot, an innovative fleet management system developed by Hodos Media. Fleetfoot utilises gamification to drive positive changes in driving behaviours, leading to safer practices, improved fuel efficiency, reduced emissions, and lower maintenance costs. The key innovation in AIPTO is the introduction of a unique software module, designed to process and analyse real-time telematics data from fleet vehicles. Using ML algorithms, this system can discern patterns in driver behaviours, fuel usage, and other essential parameters. With these insights, the module will be able to issue bespoke missions and challenges tailored to each driver's specific needs, ensuring a personalised approach that targets the most critical aspects of their performance. This level of personalisation is expected to lead to more effective skills enhancement, improved fuel efficiency, and safer driving practices. AIPTO will also investigate the feasibility of integrating real-time traffic and weather data into its mission and challenge generation process. By doing so, the project aims to provide even more refined, context-aware recommendations that could optimise routes, mitigate delays, and minimise the impact of adverse weather conditions on fleet operations. In this collaborative endeavour, Hodos Media partners with JM Clark, an operator of a nationwide commercial fleet. Utilising telematics hardware supplied by Omnia Smart Technologies, we will combine our collective expertise in software development, AI, ML, transportation research, and fleet management. With this diverse knowledge base, we aim to deliver an AI-driven solution that will benefit not only drivers and fleet operators, but also significantly contribute to the UK's broader environmental and road safety goals. The presence of real-world commercial fleet operations provided by JM Clark further strengthens the practical applicability and efficacy of the AIPTO project. Upon successful completion, AIPTO will support the UK's National AI Strategy by advancing AI capabilities within the nation and promoting a shift towards more sustainable and efficient transportation systems. The project will aid in reducing greenhouse gas emissions, enhancing road safety, and driving technological innovation in the fleet management industry. Furthermore, the widespread availability of this advanced, AI-driven solution has the potential to stimulate further advancements in related fields, generating a positive and lasting impact on the environment, economy, and society.

During various conference calls between Hodos Media Limited (Hodos), the Asian Development Bank (ADB) and Highway Management Services Limited (HMS) during Q1 2021 (on another project) there occurred some conversions around the challenges faced by the ADB in monitoring roads in developing countries, and the subject of using Remote Sensing and Earth Observation satellites was discussed. Separately, Hodos has been examining the use of a variety of approaches to monitor road and traffic conditions in developing countries. These include datasets from telematics devices from existing fleets, specifically equipped vehicles on the ground, as well as other Remote Sensing techniques. Hodos had been considering conducting a technical feasibility study to see if any of the ideas were viable before approaching funding bodies to help support a proof-of-concept project. The space based Hodos concept was to use cost-effective, low resolution Earth Observation and other Remote Sensing data to identify the major concerns and localised areas of interest, and then utilise finer resolution data to address any specific problems. After some initial "hand-cranked" projects and some analysis of historical datasets, the expectation was to build machine learning software that could be trained to quickly find issues, making it a commercially sustainable solution. Where possible other terrestrial datasets could be combined, to further optimise the system.

With the current important focus moving away from standard fuel based vehicles to electric, Local Authorities have been given targets to ensure that their operational fleets are fully electric, by 2030\. The ability to transition to an EV fleet requires the analysis of the current operation and capacity but also ensuring that the management of the services the local authority delivers is still able to be done effectively. Our project will be conducting a live demonstration with an electric Refuse Collection Vehicle (eRCV) within an actual local authority's waste collection operation, focusing on ensuring that the council will still be able to manage and complete its daily waste collection rounds using EVs. We will also be looking at how the traditional weekly collection rounds can be changed to cater for the increase in waste due to lock-down and eCommerce deliveries, and how technology can flatted demand to better suit collection using an electric vehicle.

The NetX project is seeking to address a number of key barriers to the adoption of electric vehicles (EVs); the cost of infrastructure, the ease of use of that infrastructure, and the challenging business case for investing in that infrastructure. Solving these facilitates the 'oversupply' of connectors reducing the restriction on EV drivers (or potential EV drivers) who do not have access to off-street parking (and charging). The current business model for EV charging is based around a margin on the energy sold through the network. This requires a well utilised asset and a high turnover of vehicles. This is in direct conflict with the user experience, as users will often require the parking space for longer than the charging event duration, for example a driver without off-street parking using an on-street charger doesn't want to move their fully charged vehicle at 2am. This tension prevents the investor from maximising the utilisation of their assets and in turn restricts further investment in infrastructure, and other drivers from accessing the chargepoint, both of which inhibits the take-up of EVs. A key advantage of EVs, is that by leveraging the established electricity grid, we can offer drivers the option to plug in every time they park their vehicles. This however, requires an oversupply of chargepoints, or a vehicle rotation policy. Some technology solutions have arisen around the deployment of mobile chargers linked to a battery. These however, come with the additional overheads required to move and operate the mobile charger. The NetX solution builds on the existing charger network to increase the number of access points, without requiring the installation of additional chargers, and the associated cost, until energy demand warrants it. Therefore, if the charging demand is reaching the upper limits of a NetX installation, the owner can then install more traditional chargepoints confident in the demand for them, because NetX provides visibility, unlocking a better view of the granularity of demand and type of supply required at each location. By providing end users multiple connectors from one chargepoint, linked to a smart network, we are able to both offer a significant reduction in the cost of the infrastructure, improve the user experience by removing the need to move a charged vehicle and improve the utilisation (and ROI) of existing and planned assets.

"The EV-NETX project is seeking to address key barriers to the adoption of electric vehicles (EVs); the cost of infrastructure, the ease of use of that infrastructure, and the challenging business case for investing in that infrastructure. Our current business model for EV charging is based around a margin on the energy sold through the network. This requires a well utilised asset and a high turnover of vehicles. This is in direct conflict with the user experience, as users will often require the parking space for longer than the charging event duration. This tension prevents the investor from maximising the utilisation of their asset and other drivers from accessing the charger, both inhibiting take-up of EVs. A key advantage of EVs, is that through leveraging the established electricity grid, we can offer drivers the option to plug in every time they park their vehicles. This however, requires an oversupply of chargers, or a vehicle rotation policy. Some technology solutions have arisen around the deployment of mobile chargers linked to a battery. These however, come with the additional overheads required to move and operate the mobile charger. Our solution builds on the existing charger network to increase the number of access points, without requiring the installation of additional chargers and the associated cost, until energy demand warrants it. By providing end users multiple sockets from one charging post, linked to a smart network, we are able to both offer a significant reduction in the cost of the infrastructure, improve the user experience by removing the need to move a charged vehicle and improve the utilisation of existing assets."

DASH (Delivery As a Service for Highstreets) combines multiple technology & transport partners to create a collaborative, emissions-reducing delivery proposition involving crowd-sourced deliveries & revitalisation of inner-city high-streets via an ‘easy-entry’ B2B & B2C mobile software platform. This enables: (a) utilisation of low occupancy local authority car parks as delivery hubs (X–Doc) for courier operators, with adjacent Electric Vehicle rapid charging infrastructure, (b) operators to reduce inner city courier fleets & replace with multiple crowd-sourced onward delivery options, (c) customers to have variable delivery options (B2B & B2C), (d) a scalable business opportunity for electric cargo bicycles, (e) option for taxi drivers to multi-purpose vehicles, (f) a platform for local independent high-street traders to offer goods for delivery, click & collect & drop-off points, (g) integrated pricing, payment, routing, scheduling & customer parcel tracking options. DASH is an interoperable, scalable platform technology that can be expanded to target multiple freight operators & retailers to maximise socio-economic & environmental impact.

Fleetfoot is our driver engagement and behaviour change tool for fleet telematics companies. We use game mechanics and real world rewards, combined with telematics hardware and data, to motivate and engage drivers of light commercial vehicles. Professional, safe and efficient driving is seen as a way to improve brand image for many companies. However, what does data from a safe driver look like? How can it be visualised, and how does this differ across users? What is needed to convince the insurance community? Can it be historically back-tested and will it result in a reduction of risk and lower insurance premiums for better drivers and safer operators?

Awaiting Public Project Summary

Fleetfoot is our driver engagement and behaviour change tool for fleet operators. We use game mechanics and real world rewards, combined with telematics hardware and data analytics, to engage, motivate and improve drivers of light commercial vehicles. Professional, safe and efficient driving is seen as important for brand image by many companies. We have been approached by an interntional vehicle rental company who wish to adapt our platform and convert it into a rental proposition. This will be both for professional fleet hires and consumers. We want to demonstrate that this version of fleetfoot can work in a rental vehicle environment. We want to use the driver generated data. We will visualise and transparently give the data back to the customer. By adding game concepts to this data, we can nudge better treatment of rental vehicles. The customer will receive a percentage discount from their final bill, based upon how well they have driven. This will not only make for safer driving, it will also boost fuel savings for the customer, and reduce maintenance costs for the rental company.

The Driving Data for Road Management (DD-RM) study will investigate the provision to local, regional and national government stakeholders of actionable insights for road management. It will span: • Management of remote sensing networks • Acquisition of large amounts of data • Hardware • Analysis of the data • Visualisation

The Driving Data - Exploration and Insight (DD-EI) study will investigate the provision to insurers and fleet operators of actionable insights from data. It will span: • The psychology of driver behaviour • Acquisition of large amounts of data • Hardware • Analysis of the data • Visualisation

Fleetfoot is a driver engagement and behaviour change tool for fleet telematics companies. We use game mechanics and real world rewards to motivate and engage the driver. When designed correctly, gamification has proven to be very successful in engaging people and motivating them to change behaviours, develop skills or solve problems. Leveraging some of the features used in real games, gamification can turn many other types of activities into games. Gamification is currently being applied to customer engagement, employee performance, training and education, innovation management, personal development, sustainability, health and wellness. Assigning points to activities, advancing through levels, using badges as status-markers, and integrating surprise and delight are ways to achieve wanted behaviours (Mallick, Wharton School, 2013). Business (Zicherman, Gigaom, 2013) and academic research (Hamari, Sarsa et al. 2013) proves this application of technology is not a ‘fad’ and really works.

This feasibility study will investigate the development of advanced mobile applications that intelligently understand user movement patterns. It will utilise smartphone sensors, game play and unique visualisations, to make the user more aware of their daily travel. It will encourage better use of the transport network, motivate modal shifts, reduce CO2, generate revenue and increase physical exercise.

Fleetfoot is a concept to develop a large scale game that trains and monitors Commercial drivers in ecodriving skills. Using game-like approaches to engage the end user. Goods andpeople can move around more sustainably and efficiently if everyone plays the game. When designed correctly, gamification has proven to be very successful in engaging people and motivating them to change behaviours, develop skills, or solve problems. Leveraging some of the features used in real games, gamification can turn many other types of activities into games. Gamification is currently being applied to customer engagement, employee performance, training and education, innovation management, personal development, sustainability, health and wellness. In this proof of concept we want to test if similar approaches can be used in commercial ecodriver training. Gamification can help make training more engaging and productive, because it could change how training is delivered and inspire drivers to change behaviours asa result. A game-based approach to training moves beyond traditional e-learning andsimulation training techniques.

Every significant change in the popular uptake of personal computing devices over the last thirty years has been aided by the games and activities users have discovered and enjoyed on those devices. Games such as Solitaire to Pong to Snake to Angry Birds have familiarised millions with each phase of interacting with new technology. In this project, "Gaming the mobile wallet", we propose a gamified solution to mCommerce, introducing and engaging users with the concept of virtual payments using a mobile, digital wallet. We will use the psychology of play to monitor and change behaviour. We will test two aspects of this approach. Firstly, does it generate better awareness of transactions in real time: does a more engaged spender notice fraud sooner and can they take appropiate measures to report or stop it? Secondly, can location and context aware transactions be a supporting factor for authenticating or verifying transactions? We believe that carrying out transactions on the move are important aspects to the successful uptake of mCommerce. Since you need to be moving to conduct mobile commerce. Our approach will connect the initially foreign action of “swiping” a phone to the much more familiar environment of playing and socialising on the touch screen. It will translate the phone’s physical interactions with the world into interesting, useful and meaningful digital interactions, with the emphasis on visualisations of traditionally boring financial lists of transactional data. The transaction data will be matched against the player's location. A user will be able to see and understand their spending patterns. This will also provide a level of fraud proteciton.If a user can link a transaction to a location, place or game action, it will be easier to validate that transaction. The experience will extend beyond financial transactions. It will engage users with new technology, such as Near Field Communication (NFC) use. And improve their lives with choices of healthier and more environmentally beneficial behaviours. We would be happy to work with other competition winners, who may require a more fun approach to user engagement and move away from the possible “technology push”. The game will be accessible to those who find technology difficult to access or use. The experience will be light and impactful – disposable and compulsive. Just like any good game. And finally, the user will not be particularly aware that they are the first line in fraud protection.

The Ecodriving and Gaming concept is to develop a large scale game that trains and monitors Commercial drivers in ecodriving skills, using game-like approaches to engage the end user. When designed correctly, gamification has proven to be very successful in engaging people and motivating them to change behaviours, develop skills, or solve problems. Leveraging some of the features used in real games, gamification can turn many other types of activities into games. Gamification is currently being applied to customer engagement, employee performance, training and education, innovation management, personal development,sustainability, health and wellness. In this study we wanted to test the approach in the market for commercial ecodriver training. Gamification can help make training more engaging and productive, because it could change how training is delivered and inspire drivers to change behaviours as a result. A game-based approach to training moves beyond traditional e-learning and simulation training techniques. Goods and people can move around more sustainably and efficiently if everyone plays the game.