Due to the rapid development in electronics and radio communication systems, modern technologies are implemented to improve the safety and security of workplaces in order to save field service engineers lives and their health. In this thesis, an automated safety suit was implemented with integrated sensors for monitoring the safety of field service engineers. The basic idea of the prototype is to ensure safety for the field service engineers who are working in adverse environmental conditions. This safety suit includes embedded devices which can communicate with mobile devices and by means of that provides aid for the people working in several fields such as confined spaces, high altitudes etc. In this prototype, a different type of sensors are proposed for monitoring environmental and health conditions like temperature, CO gas levels, relative humidity, body temperature and heartbeat. A mobile application is proposed to monitor and control the automated safety suit, which also identifies the environmental changes and provide prompt alerts to the user. Keeping the usage of automated safety suit in mind, the system is designed in a user friendly manner and all the key elements are considered and implemented accordingly for the requirements of service engineers who are working in confined spaces and hazardous places.

Effective construction management involves real-time decisions regarding the progress of specific activities, the location of materials and equipment, and the construction site safety. The decision making process can be improved using real-time positioning technologies such as Radio Frequency Identification Device (RFID) systems, Global Positioning System (GPS), and Ultra Wide Band (UWB) sensors. While the GPS is not applicable to indoor positioning and RFID tags cannot provide a fully automated system for position location, the characteristics of UWB systems make this technology a strong candidate for a fully automated positioning system in an indoor construction environment. This thesis presents a comprehensive study of the performance of UWB systems in a controlled laboratory environment and in an institutional construction site in Waterloo, Canada as well as for a particular safety application. A primary objective of the research was to establish the accuracy of real-time position location under various conditions, including the effect of different construction materials (e.g., wood and metal), and to analyze changes in the accuracy of position location as construction progresses and the indoor environment physically evolves. Different challenges faced in implementing such a system in an active construction environment are addressed. Based on a statistical analysis of laboratory data, and considering the construction site experience, the reliability of the UWB positioning system for the aforementioned environments is discussed. Furthermore, an automated safety system is proposed using the real-time UWB positioning technology. Based on the error modeling of the UWB position location, an optimum alarming algorithm is designed for the proposed safety system and the reliability of such system is evaluated through a statistical analysis.

Effective construction management involves real-time decisions regarding the progress of specific activities, the location of materials and equipment, and the construction site safety. The decision making process can be improved using real-time positioning technologies such as Radio Frequency Identification Device (RFID) systems, Global Positioning System (GPS), and Ultra Wide Band (UWB) sensors. While the GPS is not applicable to indoor positioning and RFID tags cannot provide a fully automated system for position location, the characteristics of UWB systems make this technology a strong candidate for a fully automated positioning system in an indoor construction environment. This thesis presents a comprehensive study of the performance of UWB systems in a controlled laboratory environment and in an institutional construction site in Waterloo, Canada as well as for a particular safety application. A primary objective of the research was to establish the accuracy of real-time position location under various conditions, including the effect of different construction materials (e.g., wood and metal), and to analyze changes in the accuracy of position location as construction progresses and the indoor environment physically evolves. Different challenges faced in implementing such a system in an active construction environment are addressed. Based on a statistical analysis of laboratory data, and considering the construction site experience, the reliability of the UWB positioning system for the aforementioned environments is discussed. Furthermore, an automated safety system is proposed using the real-time UWB positioning technology. Based on the error modeling of the UWB position location, an optimum alarming algorithm is designed for the proposed safety system and the reliability of such system is evaluated through a statistical analysis.

Predicting the future state occupancies of pedestrians in urban scenarios is a challenging task, especially considering that conventional methods need an explicit model of the system, hence introducing data-driven reachability analysis. Data-driven reachability analysis uses data, inherently produced by an unknown system, to perform future state predictions using sets, generally represented by zonotopes. These predicted sets are generally more conservative than model-based reachable sets. Therefore, is it possible to cluster previously recorded trajectory data based on the expressed behavior and perform the predictions on each cluster to still be able to provide safety guarantees? The theory behind data-driven reachability analysis, which can handle input noise and model uncertainties and still provide safety guarantees, is quite recent. This means that previous implementations for predicting pedestrians are theoretically probabilistic and would not be appropriate to implement in actual systems. Thus, this thesis is not the first of its kind in predicting the future reachable sets for pedestrians using clustered behavioral data, but it is the first work that provides safety guarantees in the process. The method proposed in this thesis first labels the historically recorded trajectories into the behavior also referred to as mode, the pedestrian expressed, which is done by simple conditional statements. This is done offline. However, this implementation is designed to be modular enabling easier improvements to the labelling system. Then, the reachable sets are computed for each behavior separately, which enables a potential motion planner to decide on which modal sets are relevant for specific scenarios. Theoretically, this method provides safety guarantees. The outcomes of this method were more descriptive reachable sets, meaning that the predicted areas intersected areas that it reasonably should, and did not intersect areas it reasonably should not. Also, the volume of the zonotopes for the modal sets was observed to be smaller than the volume of the implemented baseline, indicating fewer over-approximations and less conservative predictions. These results enable more efficient path planning for Connected and Autonomous Vehicles (CAVs), thus reducing fuel consumption and brake wear. / Att predicera framtida tillstånd för fotgängare i urbana situationer är en utmaning, speciellt med tanke på att konventionella metoder behöver uttryckligen en modell av systemet, därav introduceringen av datadriven nåbarhetsanalys. Datadriven nåbarhetsanalys använder data, naturligt producerad av ett okänt system, för att genomföra framtida tillståndspredicering med hjälp av matematiska set, generellt representerade av zonotoper. Dessa predicerade sets är generellt sett mode konservativa än modellbaserade nåbara set. Därmed, är det möjligt att dela upp historiskt inspelade banor baserat på det uttryckta beteendet och genomföra prediceringar på varje kluster och bibehålla säkerhetsgarantier? Teorin bakom datadriven nåbarhetsanalys, som kan hantera brus i indatat och modellosäkerheter och bibehålla säkerhetsgarantier, är väldigt ny. Detta betyder att tidigare implementationer för att predicera fotgängare är, teoretiskt sett, probabilistiska och är inte lämpliga att implementera i riktiga system. Därmed, detta examensarbete är inte det första som predicerar framtida nåbara set för fotgängare genom att använda kluster för beteendedatat, men den är det första arbetet som bibehåller säkerhetsgarantier i processen. Den introducerade metoden i detta examensarbete rubricerar först de tidigare inspelade banorna baserat på beteendet, även kallat läget, som fotgängaren uttrycker, vilket är gjort genom simpla betingade påståenden. Detta görs offline. Dock, denna implementation är designad till att vara modulär vilket underlättar förbättringar till rubriceringssystemet. Fortsättningsvis, beräknas de nåbara seten för varje beteende separat, vilket möjliggör att en potentiell rörelseplanerare kan avgöra vilka beteendeset som är relevanta för specifika scenarion. Teoretiskt sett så ger denna metod säkerhetsgarantier. Resultaten från denna metod var först och främst mer beskrivande nåbara set, vilket betyder att de predicerade områdena korsar områden som de rimligtvis ska korsa, och inte korsar område som de rimligen inte ska korsa. Dessutom, volymen på zonotoperna for beteendeseten observerades att vara mindre än volymen för baslinjeseten, vilket indikerar lägre överskattningar och mindre konservativa prediceringar. Dessa resultat möjliggör mer effektiv rörelseplanering för uppkopplade och autonoma fordon, vilket reducerar bränsleförbrukningen och bromsslitage.