GPS-signal Source Based on Direct Digital Synthesis

This thesis presents the design and implementation of a GPS-signal source suitable for receiver measurements. The developed signal source is based on direct digital synthesis which generates the intermediate frequency. The intermediate frequency is transfered to the final frequency with the aid of an Inphase/Quadrature modulator. The modulating GPS-data was generated with MATLAB. The signal source was duplicated to form a multi channel source. It was shown that, GPS-signals ment for civil navigation are easy to generate in the laboratory. The hardware does not need to be technically advanced if navigation with high level of accuracy is not needed. It was also shown that, the Inphase/Quadrature modulator can function as a single side band upconverter even with a high intermediate frequency. This concept reduces the demands required for output filtering.

Innovation process management of complex consumer products and services in new innovation paradigm – case location based business

Innovation is the word of this decade. According to innovation definitions, without positive sales impact and meaningful market share the company’s product or service has not been an innovation. Research problem of this master thesis is to find out what is the innovation process of complex new consumer products and services in new innovation paradigm. The objective is to get answers to two research questions: 1) What are the critical success factors what company should do when it is implementing the paradigm change in mass markets consumer business with complex products and services? 2) What is the process or framework one firm could follow? The research problem is looked from one company’s innovation creation process, networking and organization change management challenges point of views. Special focus is to look the research problem from an existing company perspective which is entering new business area. Innovation process management framework of complex new consumer products and services in new innovation paradigm has been created with support of several existing innovation theories. The new process framework includes the critical innovation process elements companies should take into consideration in their daily activities when they are in their new business innovation implementing process. Case company location based business implementation activities are studied via the new innovation process framework. This case study showed how important it is to manage the process, look how the target market and the competition in it is developing during company’s own innovation process, make decisions at right time and from beginning plan and implement the organization change management as one activity in the innovation process. In the end this master thesis showed that all companies need to create their own innovation process master plan with milestones and activities. One plan does not fit all, but all companies can start their planning from the new innovation process what was introduced in this master thesis.

Animal modelling for inherited central vision loss.

Disease-causing variants of a large number of genes trigger inherited retinal degeneration leading to photoreceptor loss. Because cones are essential for daylight and central vision such as reading, mobility, and face recognition, this review focuses on a variety of animal models for cone diseases. The pertinence of using these models to reveal genotype/phenotype correlations and to evaluate new therapeutic strategies is discussed. Interestingly, several large animal models recapitulate human diseases and can serve as a strong base from which to study the biology of disease and to assess the scale-up of new therapies. Examples of innovative approaches will be presented such as lentiviral-based transgenesis in pigs and adeno-associated virus (AAV)-gene transfer into the monkey eye to investigate the neural circuitry plasticity of the visual system. The models reported herein permit the exploration of common mechanisms that exist between different species and the identification and highlighting of pathways that may be specific to primates, including humans.

Assessing the added value of wastewater-based epidemiology to monitor illicit drug use

Wastewater-based epidemiology consists in acquiring relevant information about the lifestyle and health status of the population through the analysis of wastewater samples collected at the influent of a wastewater treatment plant. Whilst being a very young discipline, it has experienced an astonishing development since its firs application in 2005. The possibility to gather community-wide information about drug use has been among the major field of application. The wide resonance of the first results sparked the interest of scientists from various disciplines. Since then, research has broadened in innumerable directions. Although being praised as a revolutionary approach, there was a need to critically assess its added value, with regard to the existing indicators used to monitor illicit drug use. The main, and explicit, objective of this research was to evaluate the added value of wastewater-based epidemiology with regards to two particular, although interconnected, dimensions of illicit drug use. The first is related to trying to understand the added value of the discipline from an epidemiological, or societal, perspective. In other terms, to evaluate if and how it completes our current vision about the extent of illicit drug use at the population level, and if it can guide the planning of future prevention measures and drug policies. The second dimension is the criminal one, with a particular focus on the networks which develop around the large demand in illicit drugs. The goal here was to assess if wastewater-based epidemiology, combined to indicators stemming from the epidemiological dimension, could provide additional clues about the structure of drug distribution networks and the size of their market. This research had also an implicit objective, which focused on initiating the path of wastewater- based epidemiology at the Ecole des Sciences Criminelles of the University of Lausanne. This consisted in gathering the necessary knowledge about the collection, preparation, and analysis of wastewater samples and, most importantly, to understand how to interpret the acquired data and produce useful information. In the first phase of this research, it was possible to determine that ammonium loads, measured directly in the wastewater stream, could be used to monitor the dynamics of the population served by the wastewater treatment plant. Furthermore, it was shown that on the long term, the population did not have a substantial impact on consumption patterns measured through wastewater analysis. Focussing on methadone, for which precise prescription data was available, it was possible to show that reliable consumption estimates could be obtained via wastewater analysis. This allowed to validate the selected sampling strategy, which was then used to monitor the consumption of heroin, through the measurement of morphine. The latter, in combination to prescription and sales data, provided estimates of heroin consumption in line with other indicators. These results, combined to epidemiological data, highlighted the good correspondence between measurements and expectations and, furthermore, suggested that the dark figure of heroin users evading harm-reduction programs, which would thus not be measured by conventional indicators, is likely limited. In the third part, which consisted in a collaborative study aiming at extensively investigating geographical differences in drug use, wastewater analysis was shown to be a useful complement to existing indicators. In particular for stigmatised drugs, such as cocaine and heroin, it allowed to decipher the complex picture derived from surveys and crime statistics. Globally, it provided relevant information to better understand the drug market, both from an epidemiological and repressive perspective. The fourth part focused on cannabis and on the potential of combining wastewater and survey data to overcome some of their respective limitations. Using a hierarchical inference model, it was possible to refine current estimates of cannabis prevalence in the metropolitan area of Lausanne. Wastewater results suggested that the actual prevalence is substantially higher compared to existing figures, thus supporting the common belief that surveys tend to underestimate cannabis use. Whilst being affected by several biases, the information collected through surveys allowed to overcome some of the limitations linked to the analysis of cannabis markers in wastewater (i.e., stability and limited excretion data). These findings highlighted the importance and utility of combining wastewater-based epidemiology to existing indicators about drug use. Similarly, the fifth part of the research was centred on assessing the potential uses of wastewater-based epidemiology from a law enforcement perspective. Through three concrete examples, it was shown that results from wastewater analysis can be used to produce highly relevant intelligence, allowing drug enforcement to assess the structure and operations of drug distribution networks and, ultimately, guide their decisions at the tactical and/or operational level. Finally, the potential to implement wastewater-based epidemiology to monitor the use of harmful, prohibited and counterfeit pharmaceuticals was illustrated through the analysis of sibutramine, and its urinary metabolite, in wastewater samples. The results of this research have highlighted that wastewater-based epidemiology is a useful and powerful approach with numerous scopes. Faced with the complexity of measuring a hidden phenomenon like illicit drug use, it is a major addition to the panoply of existing indicators. -- L'épidémiologie basée sur l'analyse des eaux usées (ou, selon sa définition anglaise, « wastewater-based epidemiology ») consiste en l'acquisition d'informations portant sur le mode de vie et l'état de santé d'une population via l'analyse d'échantillons d'eaux usées récoltés à l'entrée des stations d'épuration. Bien qu'il s'agisse d'une discipline récente, elle a vécu des développements importants depuis sa première mise en oeuvre en 2005, notamment dans le domaine de l'analyse des résidus de stupéfiants. Suite aux retombées médiatiques des premiers résultats de ces analyses de métabolites dans les eaux usées, de nombreux scientifiques provenant de différentes disciplines ont rejoint les rangs de cette nouvelle discipline en développant plusieurs axes de recherche distincts. Bien que reconnu pour son coté objectif et révolutionnaire, il était nécessaire d'évaluer sa valeur ajoutée en regard des indicateurs couramment utilisés pour mesurer la consommation de stupéfiants. En se focalisant sur deux dimensions spécifiques de la consommation de stupéfiants, l'objectif principal de cette recherche était focalisé sur l'évaluation de la valeur ajoutée de l'épidémiologie basée sur l'analyse des eaux usées. La première dimension abordée était celle épidémiologique ou sociétale. En d'autres termes, il s'agissait de comprendre si et comment l'analyse des eaux usées permettait de compléter la vision actuelle sur la problématique, ainsi que déterminer son utilité dans la planification des mesures préventives et des politiques en matière de stupéfiants actuelles et futures. La seconde dimension abordée était celle criminelle, en particulier, l'étude des réseaux qui se développent autour du trafic de produits stupéfiants. L'objectif était de déterminer si cette nouvelle approche combinée aux indicateurs conventionnels, fournissait de nouveaux indices quant à la structure et l'organisation des réseaux de distribution ainsi que sur les dimensions du marché. Cette recherche avait aussi un objectif implicite, développer et d'évaluer la mise en place de l'épidémiologie basée sur l'analyse des eaux usées. En particulier, il s'agissait d'acquérir les connaissances nécessaires quant à la manière de collecter, traiter et analyser des échantillons d'eaux usées, mais surtout, de comprendre comment interpréter les données afin d'en extraire les informations les plus pertinentes. Dans la première phase de cette recherche, il y pu être mis en évidence que les charges en ammonium, mesurées directement dans les eaux usées permettait de suivre la dynamique des mouvements de la population contributrice aux eaux usées de la station d'épuration de la zone étudiée. De plus, il a pu être démontré que, sur le long terme, les mouvements de la population n'avaient pas d'influence substantielle sur le pattern de consommation mesuré dans les eaux usées. En se focalisant sur la méthadone, une substance pour laquelle des données précises sur le nombre de prescriptions étaient disponibles, il a pu être démontré que des estimations exactes sur la consommation pouvaient être tirées de l'analyse des eaux usées. Ceci a permis de valider la stratégie d'échantillonnage adoptée, qui, par le bais de la morphine, a ensuite été utilisée pour suivre la consommation d'héroïne. Combinée aux données de vente et de prescription, l'analyse de la morphine a permis d'obtenir des estimations sur la consommation d'héroïne en accord avec des indicateurs conventionnels. Ces résultats, combinés aux données épidémiologiques ont permis de montrer une bonne adéquation entre les projections des deux approches et ainsi démontrer que le chiffre noir des consommateurs qui échappent aux mesures de réduction de risque, et qui ne seraient donc pas mesurés par ces indicateurs, est vraisemblablement limité. La troisième partie du travail a été réalisée dans le cadre d'une étude collaborative qui avait pour but d'investiguer la valeur ajoutée de l'analyse des eaux usées à mettre en évidence des différences géographiques dans la consommation de stupéfiants. En particulier pour des substances stigmatisées, telles la cocaïne et l'héroïne, l'approche a permis d'objectiver et de préciser la vision obtenue avec les indicateurs traditionnels du type sondages ou les statistiques policières. Globalement, l'analyse des eaux usées s'est montrée être un outil très utile pour mieux comprendre le marché des stupéfiants, à la fois sous l'angle épidémiologique et répressif. La quatrième partie du travail était focalisée sur la problématique du cannabis ainsi que sur le potentiel de combiner l'analyse des eaux usées aux données de sondage afin de surmonter, en partie, leurs limitations. En utilisant un modèle d'inférence hiérarchique, il a été possible d'affiner les actuelles estimations sur la prévalence de l'utilisation de cannabis dans la zone métropolitaine de la ville de Lausanne. Les résultats ont démontré que celle-ci est plus haute que ce que l'on s'attendait, confirmant ainsi l'hypothèse que les sondages ont tendance à sous-estimer la consommation de cannabis. Bien que biaisés, les données récoltées par les sondages ont permis de surmonter certaines des limitations liées à l'analyse des marqueurs du cannabis dans les eaux usées (i.e., stabilité et manque de données sur l'excrétion). Ces résultats mettent en évidence l'importance et l'utilité de combiner les résultats de l'analyse des eaux usées aux indicateurs existants. De la même façon, la cinquième partie du travail était centrée sur l'apport de l'analyse des eaux usées du point de vue de la police. Au travers de trois exemples, l'utilisation de l'indicateur pour produire du renseignement concernant la structure et les activités des réseaux de distribution de stupéfiants, ainsi que pour guider les choix stratégiques et opérationnels de la police, a été mise en évidence. Dans la dernière partie, la possibilité d'utiliser cette approche pour suivre la consommation de produits pharmaceutiques dangereux, interdits ou contrefaits, a été démontrée par l'analyse dans les eaux usées de la sibutramine et ses métabolites. Les résultats de cette recherche ont mis en évidence que l'épidémiologie par l'analyse des eaux usées est une approche pertinente et puissante, ayant de nombreux domaines d'application. Face à la complexité de mesurer un phénomène caché comme la consommation de stupéfiants, la valeur ajoutée de cette approche a ainsi pu être démontrée.

A new approach to segmentation based on fusing circumscribed contours, region growing and clustering

One of the major problems in machine vision is the segmentation of images of natural scenes. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. The main contours of the scene are detected and used to guide the posterior region growing process. The algorithm places a number of seeds at both sides of a contour allowing stating a set of concurrent growing processes. A previous analysis of the seeds permits to adjust the homogeneity criterion to the regions's characteristics. A new homogeneity criterion based on clustering analysis and convex hull construction is proposed

Fourier-based registration for robust forward-looking sonar mosaicing in low-visibility underwater environments

Vehicle operations in underwater environments are often compromised by poor visibility conditions. For instance, the perception range of optical devices is heavily constrained in turbid waters, thus complicating navigation and mapping tasks in environments such as harbors, bays, or rivers. A new generation of high-definition forward-looking sonars providing acoustic imagery at high frame rates has recently emerged as a promising alternative for working under these challenging conditions. However, the characteristics of the sonar data introduce difficulties in image registration, a key step in mosaicing and motion estimation applications. In this work, we propose the use of a Fourier-based registration technique capable of handling the low resolution, noise, and artifacts associated with sonar image formation. When compared to a state-of-the art region-based technique, our approach shows superior performance in the alignment of both consecutive and nonconsecutive views as well as higher robustness in featureless environments. The method is used to compute pose constraints between sonar frames that, integrated inside a global alignment framework, enable the rendering of consistent acoustic mosaics with high detail and increased resolution. An extensive experimental section is reported showing results in relevant field applications, such as ship hull inspection and harbor mapping

Development of Color Difference Equations Matching to Human Vision System

Research on color difference evaluation has been active in recent thirty years. Several color difference formulas were developed for industrial applications. The aims of this thesis are to develop the color density which is denoted by comb g and to propose the color density based chromaticity difference formulas. Color density is derived from the discrimination ellipse parameters and color positions in the xy , xyY and CIELAB color spaces, and the color based chromaticity difference formulas are compared with the line element formulas and CIE 2000 color difference formulas. As a result of the thesis, color density represents the perceived color difference accurately, and it could be used to characterize a color by the attribute of perceived color difference from this color.

Learning Grasp Affordances from Vision

Monimutkaisissa ja muuttuvissa ympäristöissä työskentelevät robotit tarvitsevat kykyä manipuloida ja tarttua esineisiin. Tämä työ tutkii robottitarttumisen ja robottitartuntapis-teiden koneoppimisen aiempaa tutkimusta ja nykytilaa. Nykyaikaiset menetelmät käydään läpi, ja Le:n koneoppimiseen pohjautuva luokitin toteutetaan, koska se tarjoaa parhaan onnistumisprosentin tutkituista menetelmistä ja on muokattavissa sopivaksi käytettävissä olevalle robotille. Toteutettu menetelmä käyttää intensititeettikuvaan ja syvyyskuvaan po-hjautuvia ominaisuuksi luokitellakseen potentiaaliset tartuntapisteet. Tämän toteutuksen tulokset esitellään.

Neural mechanisms underlying conscious and unconscious vision. Evidence from event-related potentials and transcranial magnetic stimulation

Vision affords us with the ability to consciously see, and use this information in our behavior. While research has produced a detailed account of the function of the visual system, the neural processes that underlie conscious vision are still debated. One of the aims of the present thesis was to examine the time-course of the neuroelectrical processes that correlate with conscious vision. The second aim was to study the neural basis of unconscious vision, that is, situations where a stimulus that is not consciously perceived nevertheless influences behavior. According to current prevalent models of conscious vision, the activation of visual cortical areas is not, as such, sufficient for consciousness to emerge, although it might be sufficient for unconscious vision. Conscious vision is assumed to require reciprocal communication between cortical areas, but views differ substantially on the extent of this recurrent communication. Visual consciousness has been proposed to emerge from recurrent neural interactions within the visual system, while other models claim that more widespread cortical activation is needed for consciousness. Studies I-III compared models of conscious vision by studying event-related potentials (ERP). ERPs represent the brain’s average electrical response to stimulation. The results support the model that associates conscious vision with activity localized in the ventral visual cortex. The timing of this activity corresponds to an intermediate stage in visual processing. Earlier stages of visual processing may influence what becomes conscious, although these processes do not directly enable visual consciousness. Late processing stages, when more widespread cortical areas are activated, reflect the access to and manipulation of contents of consciousness. Studies IV and V concentrated on unconscious vision. By using transcranial magnetic stimulation (TMS) we show that when early visual cortical processing is disturbed so that subjects fail to consciously perceive visual stimuli, they may nevertheless guess (above chance-level) the location where the visual stimuli were presented. However, the results also suggest that in a similar situation, early visual cortex is necessary for both conscious and unconscious perception of chromatic information (i.e. color). Chromatic information that remains unconscious may influence behavioral responses when activity in visual cortex is not disturbed by TMS. Our results support the view that early stimulus-driven (feedforward) activation may be sufficient for unconscious processing. In conclusion, the results of this thesis support the view that conscious vision is enabled by a series of processing stages. The processes that most closely correlate with conscious vision take place in the ventral visual cortex ~200 ms after stimulus presentation, although preceding time-periods and contributions from other cortical areas such as the parietal cortex are also indispensable. Unconscious vision relies on intact early visual activation, although the location of visual stimulus may be unconsciously resolved even when activity in the early visual cortex is interfered with.

A Test Bed Applied Mobile Robot Navigation

It is presented a test bed applied to studies on dynamics, control, and navigation of mobile robots. A cargo ship scale model was chosen, which can be radio-controlled or operated autonomously through an embedded control system. A control program, which manages on board mission execution, is implemented on a microcontroller. Navigation is based on an electronic compass, which includes automatic compensation for pitch and roll motions. Heading control loop is based on this sensor, and on a rudder positioning system. A propulsion control system is also implemented. Typical manoeuvres as the turning test and "zig-zag", were implemented and tested. They are included on a manoeuvre library, and can be accessed independently or in combined modes. The embedded system is also in charge of signal acquisition and storing during the missions. It is possible to analyse experiments on identification of ship dynamics, control, and navigation, through the data transferred to a PC by serial communication. Navigation is going to be improved by including inertial sensors on board, and a DGPS. Preliminary tests are aimed to ship identification, and manoeuvrability, using free model tests. Future steps include extending this system for developing other mobile robots as, ROVs, AUVs, and aerial vehicles.

Weed mapping using a machine vision system

Weed mapping is a useful tool for site-specific herbicide applications. The objectives of this study were (1) to determine the percentage of land area covered by weeds in no-till and conventionally tilled fields of common bean using digital image processing and geostatistics, and (2) to compare two types of cameras. Two digital cameras (color and infrared) and a differential GPS were affixed to a center pivot structure for image acquisition. Sample field images were acquired in a regular grid pattern, and the images were processed to estimate the percentage of weed cover. After calculating the georeferenced weed percentage values, maps were constructed using geostatistical techniques. Based on the results, color images are recommended for mapping the percentage of weed cover in no-till systems, while infrared images are recommended for weed mapping in conventional tillage systems.

Automatic image-based identification of Saimaa ringed seals

The Saimaa ringed seal is one of the most endangered seals in the world. It is a symbol of Lake Saimaa and a lot of effort have been applied to save it. Traditional methods of seal monitoring include capturing the animals and installing sensors on their bodies. These invasive methods for identifying can be painful and affect the behavior of the animals. Automatic identification of seals using computer vision provides a more humane method for the monitoring. This Master's thesis focuses on automatic image-based identification of the Saimaa ringed seals. This consists of detection and segmentation of a seal in an image, analysis of its ring patterns, and identification of the detected seal based on the features of the ring patterns. The proposed algorithm is evaluated with a dataset of 131 individual seals. Based on the experiments with 363 images, 81\% of the images were successfully segmented automatically. Furthermore, a new approach for interactive identification of Saimaa ringed seals is proposed. The results of this research are a starting point for future research in the topic of seal photo-identification.

Quality assurance of refuse derived fuel with machine vision

This thesis studies the use of machine vision in RDF quality assurance and manufacturing. Currently machine vision is used in recycling and material detection and some commer- cial products are available in the market. In this thesis an on-line machine vision system is proposed for characterizing particle size. The proposed machine vision system is based on the mapping between image segmenta- tion and the ground truth of the particle size. The results shows that the implementation of such machine vision system is feasible.

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

Location intelligence strategisen päätöksenteon tukena

Kilpailuetua tavoittelevan yrityksen pitää kyetä jalostamaan tietoa ja tunnistamaan sen avulla uusia tulevaisuuden mahdollisuuksia. Tulevaisuuden mielikuvien luomiseksi yrityksen on tunnettava toimintaympäristönsä ja olla herkkänä havaitsemaan muutostrendit ja muut toimintaympäristön signaalit. Ympäristön elintärkeät signaalit liittyvät kilpailijoihin, teknologian kehittymiseen, arvomaailman muutoksiin, globaaleihin väestötrendeihin tai jopa ympäristön muutoksiin. Spatiaaliset suhteet ovat peruspilareita käsitteellistää maailmaamme. Pitney (2015) on arvioinut, että 80 % kaikesta bisnesdatasta sisältää jollakin tavoin viittauksia paikkatietoon. Siitä huolimatta paikkatietoa on vielä huonosti hyödynnetty yritysten strategisten päätösten tukena. Teknologioiden kehittyminen, tiedon nopea siirto ja paikannustekniikoiden integroiminen eri laitteisiin ovat mahdollistaneet sen, että paikkatietoa hyödyntäviä palveluja ja ratkaisuja tullaan yhä enemmän näkemään yrityskentässä. Tutkimuksen tavoitteena oli selvittää voiko location intelligence toimia strategisen päätöksenteon tukena ja jos voi, niin miten. Työ toteutettiin konstruktiivista tutkimusmenetelmää käyttäen, jolla pyritään ratkaisemaan jokin relevantti ongelma. Konstruktiivinen tutkimus tehtiin tiiviissä yhteistyössä kolmen pk-yrityksen kanssa ja siihen haastateltiin kuutta eri strategiasta vastaavaa henkilöä. Tutkimuksen tuloksena löydettiin, että location intelligenceä voidaan hyödyntää strategisen päätöksenteon tukena usealla eri tasolla. Yksinkertaisimmassa karttaratkaisussa halutut tiedot tuodaan kartalle ja luodaan visuaalinen esitys, jonka avulla johtopäätöksien tekeminen helpottuu. Toisen tason karttaratkaisu pitää sisällään sekä sijainti- että ominaisuustietoa, jota on yhdistetty eri lähteistä. Tämä toisen tason karttaratkaisu on usein kuvailevaa analytiikkaa, joka mahdollistaa erilaisten ilmiöiden analysoinnin. Kolmannen eli ylimmän tason karttaratkaisu tarjoaa ennakoivaa analytiikkaa ja malleja tulevaisuudesta. Tällöin ohjelmaan koodataan älykkyyttä, jossa informaation keskinäisiä suhteita on määritelty joko tiedon louhintaa tai tilastollisia analyysejä hyödyntäen. Tutkimuksen johtopäätöksenä voidaan todeta, että location intelligence pystyy tarjoamaan lisäarvoa strategisen päätöksenteon tueksi, mikäli yritykselle on hyödyllistä ymmärtää eri ilmiöiden, asiakastarpeiden, kilpailijoiden ja markkinamuutoksien maantieteellisiä eroavaisuuksia. Parhaimmillaan location intelligence -ratkaisu tarjoaa luotettavan analyysin, jossa tieto välittyy muuttumattomana päätöksentekijältä toiselle ja johtopäätökseen johtaneita syitä on mahdollista palata tarkastelemaan tarvittaessa uudelleen.