Excerpt
Table of Contents
1 Introduction
1.1 Thesis Structure
1.2 Background Information
2 LBS and Smart Logistics
2.1 Motivation within the Logistics Industry
2.2 Motivations for Telco Operators and LBS Providers
2.2.1 Understanding the Context
2.2.2 IMS: The Enabling Architectural Framework
3 The Role of ICT in Favour of Smart Logistics
3.1 Current Challenges and Key Drivers in the Logistics Industry
3.2 Smart Logistics based on ICT
4 Towards Smart Logistics: the LBS Approach Based on IMS
4.1 How it Works: The Logistics Provider’s Perspective
4.2 Implications for Telecom Operators and LBS Providers
4.2.1 Intelligent Network (IN) Limitations
4.2.2 Issues on Private Data Security
4.2.3 LBS Based on IMS: Implementation Requirements
4.3 LBS based on IMS: SWOT Analysis
5 Conclusion
Bibliography
List of Figures
List of Abbreviations
1 Introduction
1.1 Thesis Structure
This thesis examines the economic feasibility of potential Location-based Service (LBS) implementations in the European logistics industry, mainly for providers relying on on-road transportation. Moreover, the IP Multimedia Subsystem (IMS) should boost the realization of yet unexploited opportunities aiming at reducing fuel consumption, achieving operational savings and contributing to a low-carbon economy (e.g. reduce CO2 emissions). In this sense, IMS stands for the enabling architectural framework that combines the best of the mobile and Internet worlds: the quality and interoperability of telecom (services) with the quick and innovative development of the Internet.
From the abovementioned, this paper attempts to provide a straightforward approach to technologies enabling fuel reduction and energy efficiency through better route and load planning, among others: Smart Logistics. Within this context, Location-based Services (LBS) are an enabler for Smart Logistics by bringing location information to existing mobile applications.
The technical approach to IMS is given in [4] and therefore does not belong to the paper’s scope. In addition, the LBS approach provided in this thesis focuses primarily on road freight due to the innate saving potential in this segment compared to other ones (see Fig. 4).
Furthermore, it is well known that traditional logistic requirements, involving the transport of product from A to B at the right time and in the right condition, are no longer applicable in a multifaceted and dynamically changing logistic setting. In fact, there is a move from conventional supply chains to open supply networks. This necessarily implies that short-term business relationships tend to replace enduring ones: novel products, services and processes have to be in place for complex logistic environments. For instance, the essential adaptability and timely proactivity could be best accomplished by integrating innovative technologies, which also trigger more radical changes.
This thesis addresses in the second chapter the aspects described above by outlining the motivations for the key players within the LBS context. Next, current challenges as well as major drivers for the European logistics industry are presented prior to the introduction of Smart Logistics based on ICT. Chapter 4 describes the LBS approach based on IMS: in this section, the stakeholders’ different perspectives are depicted, emphasizing the possible application areas and related advantages.
Based on the previously described aspects, the paper then presents a SWOT analysis comprising the perception of various stakeholders. Finally, some conclusions are drawn based on the major findings and developed approach.
By the time of completion of this paper a new report, published by GeSI (SMARTer 2020), complements the previous results and estimations (discussed in SMART 2020) by providing an updated synopsis of the role ICT plays in the GHG abatement (Fig. 1)
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Figure 1: Abatement potential 2020. Breakdown of some industries.BCG analysis [29]
Fig. 1 highlights the fact that ICT has an even greater impact in society than previously assumed. What is more, it shows a more encouraging trend due to the improved abatement potential. This is for sure the starting point for different ICT-based approaches, favoring particular industries while reducing GHG emissions, like the one discussed here.
1.2 Background Information
LBS systems are context-aware services that mainly focus on using positioning as information. Particularly, LBS have grown popular following the improvement in mobile devices. According to the GSM Association [22], LBS are conceived as services that use the location of the target for adding value to the service. This ‘added value’ may comprise, within this context, the information filtering or the target display on a given map or the service activation upon a certain criteria is triggered (e.g. entering a predefined location).
Furthermore, LBS are nowadays implemented as messaging or data services relying on standards such as GPRS, WAP, etc. This, of course, does not exclude the possibility of LBS being part of conventional telephony services. Interestingly, 3GPP makes a clear distinction between location services (LS) and LBS: LS are primarily responsible for the provision and delivery of location data. In other words, LS provide the localization of targets (individuals/objects) and make them available; thus, the processing of location data in the sense of (location-based) filtering and the like is not involved. Still, LS can be considered a relevant LBS’s subservice since they contribute to the LBS operation by facilitating location data.
Furthermore, LBS are mostly regarded as a particular subset of context-aware services, which are services that repeatedly adjust their behavior depending on the target’s context. The parameters influencing this behavior are known as ‘context information’ (Fig. 2): the primary context refers to all kind of data gained from measuring elements like sensors. This data may be further combined, refined in order to generate high-level context information (e.g. secondary context) suitable for processing by context-aware services.
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Figure 2: LBS and context-aware services [21]
In this sense, LBS are usually context-aware services since location is just a particular example of context information. However, primary and secondary contexts as presented in Fig. 2 may be valid for LBS: this is the case when the history of location data is evaluated so as to get the (spatial) range between the targets (e.g. high level data retrieval). Hence, there is no strict difference between LBS and context-aware services.
In this paper, the term location refers to spatial location within the (broader) context of physical location according to [21]. For a detailed definition of physical location and its components (such as descriptive or network location) please consult this book.
In addition, this paper attempts to depict the relationship between the non-operational and operational roles associated with LBS (see Fig. 3): the potential benefits for the logistics industry as a result of the interworking with LBS/content providers and telecom operators.
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Figure 3: Roles for LBS [21]
So, the next logical question remains: Based on LBS, what is in for the logistics industry?
Nowadays, the transport of global goods is constantly increasing due to the global economic growth. In fact, the logistics of these comprehensive processes (transport, storage, among others) are naturally inefficient: on a European level, trucks are frequently partial-loaded on return journeys. Moreover, as fuel costs and taxes rise, the need for more efficient logistics operations becomes essential.
According to “Smart 2020”, a report published by The Climate Group in 2008 [29], the transportation sector is a large and growing emitter of Greenhouse Gases (GHG) and responsible for 14% of global emissions (16.5% according to [30]). This implies that optimizing logistics (based on ICT) could achieve up to a 16.5% reduction of transportation emissions and a 27% reduction in global storage emissions.
Furthermore, applications driven by ICT across logistics could accomplish a decrease in total global emissions of estimated 1.52 GtCO2 (Fig. 4). Although this figure is relatively modest compared to reductions presented by other ICT solutions in this report (Smart 2020), the opportunities to make the logistics industry more efficient have important economic considerations, since it operates such a valuable market. In 2005, the value of the global logistics industry was estimated at USD 3.5 trillion (approximately equal to the German gross domestic product in 2012, according to the IMF).
With LBS, issues like cost-effective fleet management, route optimization, inventory reduction, etc. can be best addressed. As a consequence, reduced CO2 emissions could be expected along with fuel savings for logistics providers. To put this to work in an efficient way, LBS providers and (logistics) customers demand a long-lasting, feasible and low-cost solution that clearly outweighs the initial technological and financial investments.
This could be achieved by making use of the IP Multimedia Subsystem, an architectural ‘platform’ that promises greater acceptance due to its low-cost approach and comprehensive services supply. The advantages of the implementation will be discussed in the next chapters.
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Figure 4: GHG emissions according to transport activity [35]
2 LBS and Smart Logistics
2.1 Motivation within the Logistics Industry
Smart Logistics involve a range of software and hardware tools that supervise, manage and enhance operations thus contributing to the reduction of storage needed for inventory, fuel consumption as well as kilometres driven with partially loaded vehicles. In this sense, Smart Logistics represent technologies that enable fuel reduction and energy efficiency through better route and load planning (see chapter 3.2).
Particularly, location-based services (LBS) are an enabler for Smart Logistics by bringing location information to existing mobile applications. For instance, this creates a great deal of value-added, personalized services aimed at meeting enterprise as well as user demands for improved safety and efficiency.
As already mentioned, ICT can improve the efficiency of logistics operations in different ways based on specific technologies: radio frequency identification (RFID) for asset tracking or geographical information systems (GIS) aimed at combining sensing with geographical terrain. All of these initiatives intend to enhance the communication between devices and logistics providers/suppliers. Particularly, the objective of optimizing route planning and controlling inventory for the sake of diminishing truck miles (while delivering or returning stock) remains still non-satisfying.
The main barriers behind this are:
- Logistics operators and service providers show a rather short-term approach to investment in efficiency measures.
- Lack of industry standards hampers the interoperability between various available systems (within the logistics industry)
- Regulations on competition regularly slow down possible cooperation between organizations.
Nevertheless, logistics activities are expected to grow by 23% in the timeframe 2002 and 2020 [29]. So, novel technologies and services which track effectiveness against business performance are necessary to support this development.
Besides, the European Commission has determined a 60% GHG reduction goal for the transportation sector by 2050. For the logistics industry, This appears truly challenging since its demand is likely to increase sharply within the coming 40 years [12]. With this in mind, the Commission recommends a modal shift from road to rail or water aimed at freight being transported more than 300 kms. Other alternatives under debate comprise moving away from just-in time manufacturing to the clustering of production capacities in low carbon sites, among others.
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