Water-Electricity-Light System: Technology Innovations

This paper presents the design of the Water-Electricity-Light System (WELS) that is an integration of technologies composed of rain catcher, mechanical filter and UV irradiation, solar panel, charge converter, LED light, inverter and car battery. We traced back its development from a bulky and expensive system that was meant to generate drinking water into a more innovative water cleaning system that integrated lighting and cellphone charging. We tracked the improvements applied to the system to make the design more efficient yet simple enough to be replicated and customized in order to address varied needs. We shared the alterations made to the system components based on installation experiences in different contexts. We also explored ways to lower its cost and to make its power storage more durable. Initial results are shared in this paper. Having seen its usefulness and realized its successful implementation on the ground, we are proposing the pre-positioning of WELS to promote disaster resilience in a community level. We based this assertion on the review of all documentations done and feedback gathered from our ten-year experience of more than 140 WELS installations all over the Philippines

University-Community Partnership For Water Technology Deployment And Co-Innovation: A Decade Of Engagement

The Ateneo de Manila University (Philippines), through its Ateneo Innovation Center (AIC), integrated existing simple technologies into one system – the Water-Electricity-Lighting System (WELS) – to respond to the need for potable water, lighting and communication. WELS is a portable clean water system with provision for lighting and cellular phone charging. It can be connected to a rainwater harvesting facility. Ten years of WELS deployments revealed its flexibility for customization in order to address varied water needs, especially for disaster response. Review of documentations done on past installation experiences highlights the value of engagement between university-based technology providers and community-recipients. This engagement leads to technology improvement and sustainability through co-innovation and contributes to community resilience and education through hands-on training. This paper narrates a decade of deployment experiences and presents the process of community involvement. We present a model of engaging the stakeholders that brings mutual benefit to both university and community through this partnership

Towards Laparoscopic Visual AI: Development of a Visual Guidance System for Laparoscopic Surgical Palpation

Currently, there are numerous obstacles to performing palpation during laparoscopic surgery. The laparoscopic interface does not allow access into a patient’s body anything other than the tools that are inserted through the trocars. Palpation is usually done with the surgeon’s hands to detect lumps and certain anomalies underneath the skin, muscle, or tissues. It can be useful technique for augmenting surgical decision-making during laparoscopic surgery, especially when discerning operations involving cancerous tumors. Previous research demonstrated the use of tactile sensors and mechanical sensors placed at the end-effectors for palpating laparoscopically. In this study, a visual guidance system is proposed for use during laparoscopic palpation, specifically engineered to be part of a motion-based laparoscopic palpation system. In particular, the YOLACT++ model is used to localize a target organ, the gall bladder, on a custom dataset of laparoscopic cholecystectomy. Our experiments showed an AP score of 90.10 for bounding boxes and 87.20 on masks. In terms of the speed performance, the model achieved a playback speed of approximately 20 fps, which translates to approximately 48 ms video latency. The palpation path guides are guidelines that are computer-generated within the identified organ, and they show potential in helping the surgeon implement the palpation more accurately. Overall, this study demonstrates the potential of deep learning-based real-time image processing models to complete our motion-based laparoscopic palpation system, and to realize the promising role of artificial intelligence in surgical decision-making. Visual presentation of our results can be seen on our project page: https://kerwincaballas.github.io/lap-palpation

Proton-implanted optical waveguide detectors in GaAs

Defect levels introduced by implanting GaAs with high-energy protons give rise to optical absorption at wavelengths greater than that of the normal absorption edge at 0.9 µ. Optical waveguide detectors may be fabricated by taking advantage of this absorption mechanism in the presence of a Schottky barrier depletion layer. Detector response times less than 200 ns and external quantum efficiencies of 16% have been observed

Design and Development of Electronic Sensor and Monitoring System of Smart Low-cost Phototherapy Light System for Non-Invasive Monitoring and Treatment of Neonatal Jaundice

This paper showcases our previous and continuously improving development at Ateneo Innovation Center (AIC) and partners in designing and further enhancing the existing Low-cost Phototherapy Light System (LPLS) and Improved Low-cost Phototherapy Light System (ILPLS) to the new Smart Low-cost Phototherapy Light System (Smart LPLS) with non-invasive jaundice monitoring for newborns with Neonatal Jaundice (NNJ). Developing this tool will help determine the intensity of yellowish color in infants and can monitor NNJ in a non-invasive way. The system is envisioned to be integrated with Mobile or Near Cloud as part of Smart Nursing Station together with other hospital equipment for monitoring, collection, and management of medical records and services. Its solar-power features for off-grid and remote deployments were also explored. This contribution is an extension of the Intelligent Sensors and Monitoring System for Low-cost Phototherapy Light for Jaundice Treatment that was presented in the International Symposium on Multimedia and Communication Technology (ISMAC) in 2019

Development of a Visual Guidance System for Laparoscopic Surgical Palpation using Computer Vision

Currently, there are numerous obstacles to performing palpation during laparoscopic surgery. The laparoscopic interface does not allow access into a patient\u27s body anything other than the tools that are inserted through small incisions. Palpation is a useful technique for augmenting surgical decision-making during laparoscopic surgery, especially when discerning operations involving cancerous tumors. In this study, a visual guidance system is proposed for use during laparoscopic palpation, specifically engineered to be part of a motion-based laparoscopic palpation technique. In particular, the YOLACT++ model is used to localize a target organ, the gall bladder, on a custom dataset of laparoscopic cholecystectomy. Our experiments showed an AP score of 90.10 for bounding boxes and 87.20 on masks. In terms of the speed performance, the model achieved a playback speed of approximately 20 fps, which translates to approximately 48 ms video latency. The palpation path guides are guidelines that are computer-generated within the identified organ, and show potential in helping the surgeon implement the palpation more accurately. Overall, this study demonstrates the potential of deep learning-based real-time image processing models to complete our motion-based laparoscopic palpation system, and to realize the promising role of artificial intelligence in surgical decision-making

Intelligent Sensors and Monitoring System for Low-Cost Phototherapy Light for Jaundice Treatment.

A prototype of a low-cost phototherapy light system (LPLS) was deployed by the Ateneo Innovation Center (AIC) at a public hospital in Metro Manila, Philippines. It underwent clinical investigation for two years under the supervision of licensed physicians in a public tertiary hospital. This paper presents the process of upgrading the LPLS in order to enhance capabilities and improve efficiency yet remain affordable. The following features were added: (1) a visual and auditory monitoring system in order to remotely oversee the infant from the nurse station; (2) an automation system that stores data about the device\u27s light intensity and bulb temperature and records ambient humidity; (3) an alarm system that activates the warning lights if sensor readings are in critical level and if the bulbs need to be replaced; and (4) a time setting to manually set the time of operation and automatically turn-off the device as programmed The upgrades increased the system\u27s cost but it remained cheaper than the ones commercially available. For deployment in remote or off-grid hospitals, the system was equipped with a solar-powering provision

Development of a Novel Laparoscopic Palpation System Using a Wearable Motion-Sensing Armband

This study proposes the development of a novel palpation system for use in the laparoscopic surgery setting, which relies on a wearable motion-sensing armband worn on the palpating arm. The system is tested by prodding the laparoscopic tool on a simulated human tissue with an anomaly underneath and measuring the effects of the forces experienced by the palpating arm by recording the accelerometer data embedded in the armband. Results show that the proposed system could detect the anomalies embedded in the gelatin phantom based on the change of the amplitude of the accelerometer data. A decrease in the average peak-to-peak amplitude of accelerometer signal by as much as 32.29% was observed for the single point prodding experiment, while a decrease of up to 22.93% was observed for the raster scan experiment. The results from this feasibility experiment confirmed the potential role of the accelerometer signal in the motion-sensing armband in being able to assist laparoscopic palpation

Resilient Communications and Information Systems for Disaster-Preparedness using UAVs, Beacons and Data aggregators, via Delay-Tolerant Networks on Sub-GHz Frequencies

We identified use cases where resilient communications systems may help in disaster-preparedness in the Philippines. The use cases involve critical information and communications. When networks are down due to typhoons, earthquakes and other disasters, information becomes critical. By introducing low cost and easy-to-deploy communications systems, we were able to demonstrate improved information flow in post-disaster operations. We were able to gather data seamlessly and test the range of transmission in different terrains. Using multiple UAVs, we were able to demonstrate cooperative missions between ground teams and rescue teams. The systems deployed by the team improved the flow of information without the use of legacy communications networks

Automated fish fry counting and schooling behavior analysis using computer vision

This paper presents an automated fish fry counting by detecting the pixel area occupied by each fish silhouette using image processing. A photo of the fish fry in a specially designed container undergoes binarization and edge detection. For every image frame, the total fish count is the sum of the area inside every contour. Then the average number of fishes for every frame is summed up. Experimental data shows that the accuracy rate of the method reaches above 95 percent for a school of 200, 400, 500, and 700 fish fry. To minimize errors due to crowding in the container, schooling behavior analysis is considered. The behavioral effects of different colored lights on milkfish and tilapia are thoroughly investigated. The system's effectiveness, efficiency, possible improvements, and other potential applications are discussed