Dissolved Oxygen (DO) in water enables marine life. Measuring the prevalence of DO in a body of water is an important part of sustainability efforts because low oxygen levels are a primary indicator of contamination and distress in bodies of water. Therefore, aquariums and aquaculture of all types are in need of near real-time dissolved oxygen monitoring and spend a lot of money on purchasing and maintaining DO meters that are either expensive, inefficient, or manually operated—in which case they also need to ensure that manual readings are taken frequently which is time consuming. Hence a cost-effective and sustainable automated Internet of Things (IoT) system for this task is necessary and long overdue. DOxy, is such an IoT system under research and development at Santa Clara University’s Ethical, Pragmatic, and Intelligent Computing (EPIC) Laboratory which utilizes cost-effective, accessible, and sustainable Sensing Units (SUs) for measuring the dissolved oxygen levels present in bodies of water which send their readings to a web based cloud infrastructure for storage, analysis, and visualization. DOxy’s SUs are equipped with a High-sensitivity Pulse Oximeter meant for measuring dissolved oxygen levels in human blood, not water. Hence a number of parallel readings of water samples were gathered by both the High-sensitivity Pulse Oximeter and a standard dissolved oxygen meter. Then, two approaches for relating the readings were investigated. In the first, various machine learning models were trained and tested to produce a dynamic mapping of sensor readings to actual DO values. In the second, curve-fitting models were used to produce a successful conversion formula usable in the DOxy SUs offline. Both proved successful in producing accurate results.

Many agricultural Internet of Things (IoT) solutions focus on the monitoring and management of water in irrigation or storage systems. The hydration automation (HA) automated water monitoring and management system utilizes low cost, small form factor, and sustainable sensing units (SUs) to collect water level reading of water storage systems through the use of an ultrasonic sensor and actuating units (AUs) for automating the control of valves and pumps that are operated via a Base Station. The SUs and AUs are housed in water proof, cost-effective, and environmentally friendly custom-built 3D printed casings and often placed miles away from each other in agricultural lands. This necessitates the existence of a long-range communication subsystem which utilizes the ÂB communication protocol atop of LoRa or other link layer protocols. This setup of the HA system, effective for monitoring and operating multi-tank irrigation systems, is however an overkill for systems comprising only a single water tank. Furthermore, the HA system thus far had not included a mechanism for remote emptying or decreasing of the existing water levels of water tanks. A capability that is, for instance, needed for preventing damage to the tanks when freezing of the water is possible. This paper discusses the implementation of a smart tank for the HA system which comprises an AU for water level control automation and is controlled directly by a minimally enhanced SU rather than a specialized Base Station.

—The status of crops, water tanks, and various other components of modern agricultural irrigation systems can be sensed and valves and pumps can automatically be actuated to ensure the distribution of adequate water to all parts of the system. In previous work, we have discussed the design and implementation of low cost, small factor, and sustainable Sensing Units (SUs) which use ultrasonic sensors to measure the available empty space in a water tank and communicate the water levels to the Actuating Unit (AU) they are assigned to, so that the AU can operate the valves and/or pumps necessary to send the exact amount of water needed to restore the tanks’ designated water levels. There, we indicated that a future step is the redesign of the circuitry in order to shrink the overall size of the SU, increase its energy efficiency, and enable the addition of new environmental sensors such a temperature sensors that can warn the users or take automated action when the freezing of the water in the tanks is predicted and/or sensed. Also, in previous work we have discussed the design and 3D Printing of a water proofed, cost effective, and environmentally friendly custom encasement for the SUs and indicated that a next step is to redesign the internals of the SU casing in order to allow for the addition of new components while reducing the size of the casing as an effort to reduce the amount of material used and hence enhance the system while further reducing the SUs’ cost. This paper is to report on the success of all these steps and more which collectively enable the production of a marketable smart agricultural environment monitoring SU for irrigation automation.

Diabetics are used to pricking their fingertips in order to check their glucose level. In an effort to sunset that practice, Santa Clara University’s Ethical, Pragmatic, and Intelligent Computing (EPIC) Laboratory has envisioned, designed, and prototyped a portable noninvasive glucose monitoring medical instrument which we have dubbed GluMo. In place of a drop of blood GluMo uses Infrared (IR) light emitters and receivers as part of a small form factor Internet of Things (IoT) medical instrument which calculates the amount of the IR wave’s interaction with glucose molecules within the blood stream. The information is then transmitted to a database for tracking, history building, and data visualization for the patient (and potentially the patient’s doctor if authorized). Since current single droplet blood glucose meters are attainable as cheap as 10 USD, in order to keep GluMo’s cost under 100 USD without diminishing the accuracy of the reading outside of an acceptable bounds, Near Infrared (NIR/IR-A DIN) emitters at the 1300 nanometer (nm) wavelength and corresponding receivers were chosen for the prototype. The choice of 1300nm NIR/IR-A comes from the fact that 60% of human blood is water (H2O) and 1300nm NIR/IR-A has the largest positive difference between its absorbance in glucose and its absorbance in water among the other wavelengths of IR in the NIR/IR-A range. Keywords–Blood Glucose Monitor; Infrared (IR); Internet of Things (IoT); Medical Instrumentation; Non-invasive.

ÂB is an Energy Aware Communication Protocol (EACP) prototype which has been developed for the communication subsystem of Hydration Automation (HA)—an agricultural Internet of Things (IoT) system currently under research and development at Santa Clara University’s Ethical, Pragmatic, and Intelligent Computing (EPIC) laboratory.

Plankton provides an essential foundation for life on Earth, supplying most of the breathable oxygen, carbon sequestration, and larvae nutrition. Toxic chemicals introduced into the environment pose a potential danger to plankton and the ecosystem. Traditional plankton chemical toxicity assays measure the concentration required to cause death. Sublethal doses that affect plankton activities like foraging and escaping predators can have a cascading impact on ecosystems. We have developed a high-throughput device to measure the sublethal effect of chemicals on the plankton rate of movement. The device automatically creates a series of chemical dilutions, subjects each concentration to a group of plankton, and calculates the average group movement speed. We tested the device on groups of Stentor coeruleus (n=3 to 26, mean=10) with acetic acid dilutions (43 to 25,000 ppm) and measured a declining trend in average speed with increasing sublethal concentrations (170 to 502 ppm).

Harvesting of honey is a laborious job which requires the daily inspection of every frame within every hive of every apiary. Apiaries are easily scalable via the addition of new hives or the addition of expansion boxes to existing hives but the scaling of human labor to meet the added work needed to inspect, harvest, and maintain the added frames is costly and often nonexistent. Existing Internet of Things (IoT) beekeeping and monitoring systems on the market are very costly and do not provide per-frame information to beekeepers. Although they are successful in generating a slew of useful information regarding the strength, condition, and even overall honey yields of a hive over time, they fall short in enabling beekeepers to know exactly which frames are ready for harvesting without a physical inspection of each. Therefore, they neither contribute to the labor reduction associated with harvesting nor are they effective in the prevention of swarming, a condition where a hive colony reproduces via exiting the hive and leaving behind the larvae of the next generation - thus halting honey production. The only way to truly reduce honey harvest labour and swarming is to collect per-frame weight data which is a complex and costly task and has therefore been avoided in existing solutions. Our initial results in collecting per-frame weight have confirmed the complexity and costliness of this task though have also provided us with a clear path to the reduction of both the complexity and cost of a per-frame harvesting scheduler. We utilized low cost off-the-shelf force sensors along with a mathematical model for data normalization which produces accurate data. However, the complexity and cost must still be reduced via the design and development of new custom sensors in order to create a viable and marketable product.

Farms, greenhouses, orchards, ranches, and vineyards are all dependent on irrigation systems. Modern irrigation systems are equipped with an assortment of water reserves, sheds, and tanks to store water for later use or to manage the flow, time, or quality of the water delivered to the crops. In comparison to expensive, huge, complex, proprietary, cloud dependent, often manual, and very energy hungry industrial solutions out on the market, Hydro-System Automation (HA) is a cheaper, smaller, simpler, modular, smart, and sustainable Hydro-System. The design entails sensing and actuating units as well as a wireless communications subsystem between said units. The Sensing Units (SU) s are composed of cheaper, smaller, simpler, and more sustainable sensors, micro-controllers, electronics, solar panels, and batteries than those used in current industrial solutions available. Future SUs will be packaged in 3D-printed casings which are cheaper to produce, can be custom fabricated to incorporate specific designs, fit in tight spots, and meet a variety of environments, installation requirements, and quality standards. The Actuating Units (AU) s are composed of automated pumping and/or valve stations which are powered via solar panels. The wireless communications sub-system is responsible for maintaining the overall cohesion of the system via a custom routing protocol atop a transport layer such as LoRa and a wireless physical layer utilizing RFM95 Radio Modules in the 915/916 MHz frequency band. Prototypes of the SUs have proven the cost effectiveness, simplicity, and energy efficiency of their design.

Roadways play an essential role in today’s society by contributing to economic growth and development, providing access to all members of society and fast routes to travel on efficiently. With increased numbers of vehicles on the roads, the quality of the roads is deteriorating at a faster rate than can be maintained and repaired. This decrease in road health materializes as hazards such as potholes that can cause significant damage to vehicles on the road. Currently, roads’ health is monitored manually and thus done infrequently due to it being both time-consuming and costly for the responsible local transit authorities. Therefore, many road quality issues are repeatedly reported by the people who drive on them before any inspection or repair efforts are undertaken by the transit authorities. This manual process of reporting potholes and other road hazards is an inefficient process requiring filling out forms or making phone calls while remembering the exact location of the pothole or road hazard. This chapter presents Drive Health, an Internet of Things (IoT) system developed to crowdsource the monitoring of the health of roadways by informing transit authorities of pothole locations. Drive Health includes a smart sensor and performs machine learning on accelerometer data to process and analyze the data without using the cloud. If the system determines that the data indicates the existence of a pothole, the location of where the data was collected is recorded and sent to a web server which can then be automatically shared with the transit authorities responsible for that road location.