The overarching innovation of the FIspace project is the FIspace platform, which is an extensible SaaS cloud offering that can be extended by means of (1) adding functionality through Apps, (2) defining collaborative processes, (3) integrating data sources of users. Beyond the concrete technical realization of the FIspace platform, which required several technology innovations, the concept of the FIspace platform also triggered the incubation of innovations on top of such platform concept. As part of the FIspace project, many individual innovations have been made. Many of those were essential to delivering the FIspace platform, others were triggered by the FIspace platform itself. This section describes these individual innovations of the FIspace project as reported by the project members.
The innovations are structured along four main clusters:
The following sections provides a summary of the innovations. A more detailed description of these innovations can be found by clicking on the respective links, which will download a Word document with more information.
| Name | Summary |
|---|---|
| A1 Improved Shopping Experience App | The Apps provides clients with a set of functionalities in just one app which will make their shopping experience much easier than before. All these functionalities have been developed in Android and iOS in order to obtain a better market acceptance. Consumers can manage their shopping lists by adding real products from the supermarket. Moreover, the app even suggests different recipes based on consumer preferences and health information. Consumers can access tailored product information at the supermarket via the mobile device by means of augmented reality. Furthermore, customers will receive real time information from the supermarket about the best offers and alerts. What is more, they can send feedback about the products to the supermarket. |
| A2 Fresh Food Transparency Apps | The transparency Apps for fresh food, in particular meat, have been developed based on the new EPCIS standard that can handle irrevocable events, e.g. a slaughtered cow can never become alive again or even one single piece as it was in the beginning. The Apps are based on a system that consists of one or more EPCIS repositories that contain all events of a meat item starting at the farm, and subsequently passing the slaughterhouse, meat processors, distributors and or cold store to arrive finally in the supermarket. |
| A3 Consumer Goods Import/Export Apps | This innovation is concerned with planning and execution of logistics activities in the consumer goods sector ensuring effective planning of related activities resulting in improved coordination, loss minimization, efficient use of resources and high customer satisfaction level. Effective planning and timely monitoring of the transportation process is crucial since unexpected delays might lead to problems and losses in several stages starting from the production activity till the delivery of finished goods to the customers. It improves collaboration between different stakeholders during the transport demand description process and it makes information available to users till the end of the execution of the shipment. |
| A4 Cargo-SwApp | In the short sea container market, the carriers face problems as low visibility and predictability of the transport demand, low customer loyalty and a high number of late transport booking cancellations, mostly due to lack of collaboration or access to information. This results in short time windows to find new cargo, extra work on re‐planning and sub‐optimal use of transport capacity. It is common that 30‐40% of cargo is cancelled close to the cut-off time. The CargoSwApp was developed to cope with these late cancelations and enable carriers to quickly react and find replacement. CargoSwApp also offers the possibility to assess each booking, and enable the carrier to anticipate cancellations, thus using overbooking in a more effective manner. By extending the scope of the CargoSwApp, functionalities for shippers have also been added: the possibility to search the marketplace via CargoSwApp and benchmark service offers at shipment level. CargoSwApp allows for immediate information exchange between shipper and carrier. |
| A5 Botanic Trading Information App | The prototype Botanic App offers valuable trading information to professional growers and traders in flowers and plants. It offers anytime and anywhere access to the correct taxonomic product descriptions, trading codes (VBN codes) and availability throughout the year. Reduction of errors in communication and ordering is expected, which enhances the efficiency in the supply chain. |
| A6 RISKMAN App | RISKMAN significantly differs from other warning systems. RISKMAN offers a collection of structured (contracted laboratories, public authorities (i.e. EFSA)) and unstructured information items (i.e. social media networks) in order to provide a collection of potential information on risks in the distribution of fruits and vegetables to the users of the app (i.e. risk man-agers of agri-food companies). It therefore represents a special and innovative type of news center for critical information on food safety, which we consider as an early warning system. | A7 BizSLAM App | BizSLAM is a cloud-based software component that automatically manages multi-level SLAs by extending SLA management solutions from service-oriented computing. SLA management of transport and logistics services significantly differs from SLA management of cloud or web services due to the important role that frame SLAs play in contracting. A frame SLA is a general agreement that constitutes a long-term contract between parties. The terms and conditions of the frame SLA become the governing terms and conditions for all specific SLAs established under such a frame SLA. Not considering the relationships between frame SLAs, specific SLAs and QoS monitoring information may lead to partial conclusions and decisions, thereby resulting in avoidable penalties. BizSLAM delivers a multi-level run-time SLA management approach for transport services that takes into account those relationships. | A8 Bad Weather Warning App | Different fumigation products have optimal application conditions, drying time, absorption rate and retention time. For that reason, sprayer operators seek a lot of information about the weather and the environment with of high accuracy (up to field level). To achieve this goal, the Workability Data App has design and develop an automated decision-making prediction module which shall help the farmers to decide the most suitable period for their spraying activities and notify them if the forecast prediction has changed. The App calculates the spraying conditions for a particular location based on the criteria specified by the farmer and the chosen dataset containing the weather predictions (wind speed / direction, probability / type and intensity of rainfall, temperature, humidity, etc). Once the spraying activity has been planned (using the scheduling app), this App module gathers the information in order to periodically check that the weather prediction updates don’t affect the scheduled activity workability. Depending on the preferred weather provider, the App can check the forecasts several times per hour. If the value changes significantly, for example not allowing for the execution of the spraying, this module will send a push notification to the farmer mobile terminal and other selected platforms, reporting him about this unforeseen event. It allows re-starting the cycle if the farmer deemed it appropriate | A9 Traffic Light App | The Traffic Light App allows supermarket customers to access important information about certain product attributes they might find useful. The app shows in a clear way whether the attribute associated to the product is in a dangerous level, a normal level or a good level based on rules previously de-fined. An administrator can create and later update these rules if necessary. The customer asks for information using the product id and sends the request to the server that searches for the product information and applies the rules. The information is then shown on the screen where each attribute is coloured in green, yellow or red based on whether it is considered good, normal or dangerous, respectively. The innovation of this approach relies on the provision of rules in product information making the application configurable and adaptable to other conditions or food parameters. | A10 BOXMAN App | BOXMAN is a first App that reaches beyond enterprise borders and realizes a chain encompassing management of packaging (crates, boxes) across the whole food chain reaching from production agriculture until retail. All enterprises are involved in reporting the movement of crates (in and out) while the central box management company assures that demand of boxes by enterprises are met at all times and that empty boxes are cleaned upon being returned by retail companies. Despite the chain encompassing management application, each company runs its own web-based application which is linked to the box management group. The App provides transparency on the carriers of products which provides the basis for other applications such as tracking and tracing of products, the identification of origin, the monitoring of product quality, etc. | A11 Product Information (PIA) App | PIA is an application that reaches beyond enterprise borders and realizes a chain encompassing exchange of information between actors across the whole food supply chain, reaching from production agriculture to retail. This application provides a solution for many problems the food chains are presently experiencing. It provides transparency across the chain on product characteristics, product quality, characteristics of production processes (e.g. inputs in agricultural production), logistics, tracking and tracing needs, and more. It also provides the basis for monitoring product quality and deliveries along the chain. At retail, PIA provides the interface for applications that communicate information to consumers. Beyond its reach across the chain, its innovation is in the separation of the information exchange into a sequence of individual apps that are run by individual enterprises, i.e. it is not based on a central data management approach. This innovative decentralized data management approach, enabled by the FIspace platform, overcomes a core barrier for adoption of information exchange solutions by the food sector. | A12 Tailored Information for Consumers Apps (TIC) | This App complements the B2B PIA App by providing an end-user interaction and visibility to the supply chain. One important concern is the provisioning of accurate information to individual consumer´s needs. Two complementary Tailored Information for Consumers Apps address this concern. The TIC App’s main objective is to collect and store links of the different product information providers. This information can be made available to other Apps through the FIspace platform capabilities. The TaPIA App’s main objective is to provide to consumers static and dynamic information of a product according to a profile where each consumer can choose which product attributes he/she want to know. This mobile application is adapted to each profile and range of information needs of consumers. |
| Name | Summary |
|---|---|
| P1 FIspace Studio | FIspace Studio is the Software Development Kit (SDK) that provides tool-support for the development of FIspace Apps. The SDK eases the work of App developers during the implementation of the Apps, providing specific tools and hiding the complexity of the platform. Also the Business Process architects find the proper way to manage the business entities at FIspace platform. The SDK for FIspace consists of a collection of Eclipse plugins available to be installed and the FIspace Studio Tool (which is the binary distribution of such plugins). Also, a set of libraries implemented in several programming languages provides the FIspace user with the appropriate tool to connect to the platform. FIspace Studio Tool is represented by an Eclipse Rich Client Application. The distribution provides the required user interface for all of the pre-installed FIspace SDK functionalities along with a customized approach of the Eclipse IDE reaching the specific needs of FIspace platform. |
| P2 Business Process Collaboration and Complex Events | In today’s competitive and dynamic landscape, business managers are continuously forced to effectively react to any event that has the potential to affect the expected course of their business processes. To cope with this requirement, companies are increasingly adopting business process engines alongside with event processing engines, to manage their business process and get real-time alerts once a situation requiring a course of action occurs. However, these two engines deal with different business logic and programming models and, as result, integration between the two is far from being easy. Business process engines are usually synchronous and the process encompasses sequential steps or tasks to be performed. Event processing engines are by nature asynchronous. Events can happen in any order and an action is taken in a reactive mode. The B2B component in FIspace, composed of a business collaboration module (BCM) and a (complex) event processing engine (EPM), offers a seamless integration between these two types of engines. The artefact-centric approach for business processes is reactive and asynchronous, and events are the ones responsible for the progress in the flow. Moreover, the programming model of the BCM supports the inclusion of events as a building block in the programming model making the integration easy. While the event logic is done within the EPM, the output events can be guards and milestones in the BCM programming model. |
| P3 Ygg: Capability-driven Cross-Organizational Business Collaboration | The core functionality of Ygg is to facilitate business to business collaboration. The main way Ygg supports this is via business processes. Characteristic of these business processes is that they exceed the boundaries of one business. All Ygg core components are involved in supporting those business processes. A business process in Ygg is implicit. This means you don't have to define or describe one explicitly. A process actor only has to define in Ygg that he is capable of providing a specific service. A different actor then can in turn use this capability. This introduces the concept of capability. The benefit of using capabilities is that all capabilities providing similar services would look the same. That way an actor would be able to switch from one service to another without making a lot of adjustments in his software. For this reason Ygg contains a registry with defined capability types. |
| P4 Composite Service Bus | The Composite Service Bus (CSB) is a middleware that enables integration of different FIspace service components and applications. CSB provides a set of integration interfaces and qualities of service, required to support a wide spectrum of information exchange scenarios, ranging from best effort notifications, to guaranteed delivery of transactional data. CSB has virtually unlimited scalability, both in the number of supported end-points, and in the number of communication channels allowed by the Bus transport fabric. The scalability challenge, posed by the large number of data producers, service providers and consumers in this cloud-based project, is addressed by Peer-to-Peer overlay technology. The CSB core is comprised of Bus Nodes, connected by a peer2peer structured overlay fabric. The CSB clients are the FIspace service components, using the Bus for integration and connectivity. This two-tier architecture allows us to build an enterprise-strength service bus, with extensive functionality set and assured delivery of transactional data. |
| Name | Summary |
|---|---|
| I1 Low Cost Wireless Sensor Network based on Open Hardware | To engage small-medium farmers into next generation agricultural processes, it is essential to present them with products and services that have as low entry cost as possible. To this end, a simple, effective and low cost wireless sensor network deployment was needed so that farmers will benefit the most from what a platform such as FIspace has to offer. However it is often the case that sensor network equipment is really expensive and is only compatible with the vendors’ software management solution. This leads not only to vendor lock-in, but also extends the investment depreciation far back in time. By utilizing open hardware and low cost Arduino-based solutions, along with several sensor integration and hardware modifications activities, we were able to develop a significantly lower cost wireless sensor network, targeted at small farms. The wireless sensor network is accompanied by software modules for management of the gathered values, as well as being able to communicate these measurements to other platforms via the web. |
| I2 Real-Time Cargo Volume Recognition | Transport and logistics faces fluctuations in cargo volume that statistically can only be captured with a large error. Observing such dynamic volume fluctuations more effectively and providing the data about volume fluctuations in real-time promises many benefits for better management of transport processes, such as reducing unused transport capacity and ensuring timely delivery of cargo. We combine a mobile App with internet-connected (IoT) sensors to deliver up-to-date, timely, and precise information about parcel volumes inside containers. In particular, we introduce a novel approach for employing internet-connected low-cost, off-the-shelf 3D scanners (Microsoft kinect) for capturing and analysing actual cargo volumes. Accuracy of volume recognition as been evaluated in controlled experiments indicating that cargo volume can be measured with high accuracy. In addition, a survey study with domain experts revealed its high potential for practical use. |
| Name | Summary |
|---|---|
| X1 Linked Pedigrees | An entirely new approach to tracking and tracing in the supply chain based on an integration of GS1 standards with Semantic technology. Aston has formalised the GS1 EPCIS standard in a series of formally rigorous ontologies (EEM, CBV) and provides a Java library. Together with a rigorous architecture, this enables actors along the supply chain to record events as "linked pedigrees" in individual separate triple stores which providing URL links to corresponding pedigrees upstream in the supply chain. This enables each actor to keep complete control of their data while enabling total tracking, tracing and transparency to appropriately authorised actors (e.g. regulators or retailers). The main benefit of this approach is opportunity for multiple software developers to provide light-weight but interoperable systems for data integrations across the supply chain |
| X2 Floriculture Logistic Label and Business Rules | When transporting flowers and plants, such as in the Netherlands, often an ‘auction delivery note’ is used. The delivery note identifies each load carrier and as such the flower or plant lots which are on that load carrier. More and more often however this auction delivery note is no longer used for the transport of flowers and plants. E.g. when delivering large lots from grower direct to retailer. Or deliveries of non-auction growers and the transport from one auction location to another location of lots bought via KOA (Remote Buying). And finally also the transport from the wholesale trader to his customers in the country and abroad. The innovation covers a set of business rules as to how these transports can be performed at best, building on the standard Floriculture Logistic Label. |
| X3 Predictive Transport Process Monitoring | Predictive business process monitoring aims at forecasting potential problems during process execution. Predictive business process monitoring thereby facilitates handling these problems proactively before they occur. We adapt and tune three main classes of predictive monitoring techniques to the problem of forecasting transport process instances. In particular, we show that machine learning, constraint satisfaction, and Quality-of-Service (QoS) aggregation can be used for transport prediction and that we can consistently achieve a prediction accuracy of more than 70%. To improve the prediction process, we exploit the characteristics of the individual techniques and define an ensemble of these techniques. Evidence indicates that this may, for instance, improve precision by 14% or recall by 23%. |