Light-Based IoT-Enabled Battery-Free Active Product Monitoring for Sustainable Smart Packaging Applications

Light-Based IoT-Enabled Battery-Free Active Product Monitoring for Sustainable Smart Packaging Applications Amila Perera1and Marcos Katz1 1Centre for Wireless Communications, University of Oulu, Finland This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. Abstract Product wastage due to inadequate condition monitoring during storage and transport remains a significant challenge in modern supply chains, particularly for perishable goods. Conventional packaging systems often lack real-time visibility and rely on battery-powered electronics, which pose sustainability and scalability issues. To address these limitations, this work presents a sustainable smart packaging system based on Light-based Internet of Things (LIoT) architecture, termed LIoT-based Active Smart Packaging (LIoT-ASP). The proposed solution integrates Photovoltaic Energy Harvesting (PV-EH) and Optical Wireless Communication (OWC) to enable battery-free, energy-autonomous operation for product condition monitoring in retail and logistics environments. A prototype system was developed using commercially available components, incorporating both visible light downlink and infrared uplink channels based on consumer device IR protocol-inspired OWC, adapted for low-power operation. The bidirectional OWC supports a data rate of 1.1 kbps, sufficient for periodic sensing and display updates in low-throughput smart packaging applications. The system employs energy-aware control mechanisms and intermittent operation strategies to manage sensing and data communication under variable indoor illumination. Performance of the LIoT-ASP concept was assessed through the developed proof-of-concept prototype system, followed by experimental validation in a real-world scenario involving temperature-sensitive dairy products. The system successfully detected and reported threshold violations via cloud-connected mobile alerts, demonstrating reliable end-to-end functionality. These findings validate the practical feasibility of deploying LIoT-ASP systems as a sustainable and scalable solution for smart packaging applications. Light-based IoT, Smart packaging, Optical wireless communication, Energy harvesting, Battery-free IoT, Visible light communication, Sustainable wireless communications. 1 Introduction With the advancement of 6G and next-generation communication technologies, sustainability has emerged as a fundamental Key Performance Indicator (KPI) for future Internet of Things (IoT) systems [1]. In this context, IoT sensor networks play a pivotal role by facilitating real-time monitoring and accurate data acquisition, which are essential for achieving environmental sustainability objectives across diverse application domains [2]. In the domain of food and consumer goods, storage and packaging are critical for maintaining product quality within acceptable parameters throughout the entire life cycle, while also supporting marketing functions. Traditional packaging methods typically rely on static expiration dates, providing only approximate estimations of product condition. This absence of dynamic, real-time information may expose consumers to food-borne illnesses due to the consumption of unsafe or degraded products [3]. In order to address these limitations, concepts of active and intelligent food packaging have been proposed, with legal and safety concerns gradually being assessed and standardized over time [4,5]. Smart packaging employs IoT technologies by incorporating sensors such as Time-Temperature Indi1 cators (TTIs) and gas sensors to enable real-time monitoring, traceability, and enhanced safety features. These sensors facilitate interactive feedback mechanisms that dynamically communicate the product’s condition through the packaging interface [6,7]. As a result, intelligent systems are being developed to continuously monitor and report product status during storage and transport. These advancements are essential in addressing critical challenges related to product integrity, consumer safety, and waste minimization across sectors handling temperatureor condition-sensitive goods. Particularly in food and pharmaceutical applications, modern packaging increasingly integrates biosensors, freshness indicators, and real-time traceability platforms to enhance supply chain transparency and reduce environmental impact [6,8]. However, the majority of IoT-enabled smart packaging solutions currently rely on Radio-Frequency Identification (RFID) technologies, including battery-free passive tags, battery-assisted semipassive tags, and fully active battery-powered RFID systems [9–11]. In large-scale RFID deployments, the omnidirectional nature of Radio Frequency (RF) communication can cause reader collisions, where overlapping reader signals lead to interference, increased latency, and tag misreads, thereby demanding additional coordination mechanisms and increasing system complexity to mitigate these issues [12]. While widely used for identification and tracking, passive RFID devices are generally limited to single-function operation and lack support for continuous sensing or autonomous functionality. Battery-powered variants, although capable of active sensing, may perform sub-optimally in environments where low temperatures affect battery efficiency and reliability [13]. A more significant concern is their limited sustainability, as these systems require periodic battery replacement or maintenance [11]. This dependence introduces substantial challenges for large-scale consumer product applications due to sustainability concerns linked with electrochemical energy storage. The widespread use of batteries imposes considerable environmental and economic burdens, including high energy consumption associated with raw material extraction, manufacturing, transportation, and end-of-life recycling. Consequently, battery-reliant designs counteract the very sustainability objectives that smart packaging seeks to support [14]. Meanwhile, the development of energy autonomy in IoT systems has inspired the development of Lightbased IoT (LIoT) architectures, which utilize indoor illumination for both Photovoltaic based Energy Harvesting (PV-EH) and Optical Wireless Communication (OWC) [15–17]. These systems are particularly applicable to settings with existing illumination infrastructure, such as supermarkets, cold chains, and storage facilities, which are common environments for smart packaging deployment. By harvesting indoor light, LIoT designs eliminate the need for electrochemical batteries, thereby enabling zeromaintenance operation and advancing sustainability goals. Furthermore, OWC enables communication over the unlicensed optical spectrum, offering advantages such as physical-layer security and immunity to electromagnetic interference [15]. These benefits are particularly valuable in high-density environments where conventional RF communication may encounter interference and spectrum congestion. The integration of OWC into smart packaging supports reliable and interference-resilient communication in such large-scale applications. In addition, the hybrid integration of conventional electronics with sustainable technologies such as printed electronics further enhances ecological performance. Printed components, compatible with low-cost and energyefficient fabrication techniques, are especially suitable for large-area or flexible modules in smart packaging nodes [15]. This combination supports scalability and aligns with the principles of circular and sustainable product design [18]. This research builds upon earlier work [15–17], which established the foundational concept and feasibility of LIoT for energy-autonomous communication. The present study advances this foundation by integrating a battery-free LIoT architecture with active smart packaging functionality, resulting in a sustainable and optically communicating packaging solution, referred to as LIoT-based Active Smart Packaging (LIoT-ASP). Specifically, this work extends previously proposed LIoT designs [16,17] from componentlevel feasibility studies to a fully integrated end-toend smart packaging system that includes application based validation, real-time monitoring, and cloud connectivity. The key contributions of this work are as follows: •Develops a battery-free LIoT-ASP system that integrates PV-EH, OWC, and energy aware intermittent operation strategy, enabling dynamic task scheduling and cloud connectivity under 2 variable indoor illumination. •Validates system performance in a cold-chain use case with temperature-sensitive goods, demonstrating autonomous sensing, robust IR-based uplink, and flicker-safe VLC compliant with standards, building on established IR protocols and LIoT design frameworks. The remainder of the article is organized as follows: Section II introduces the proposed system model; Section III discusses the design considerations and implementation challenges; Section IV details the prototype implementation used for evaluation; Section V presents the performance evaluation; and Section VI concludes the paper. 2 System Model Designing sustainable IoT systems for indoor environments requires a careful balance between energy availability, communication efficiency, and compact system integration. LIoT offers a compelling solution in this context by combining PV-EH with OWC, particularly using VLC for downlink communication. This dual-purpose approach enables energyautonomous operation while simultaneously exploiting existing illumination infrastructure for data communication [15–17]. A key consideration in the design of indoor LIoT systems is the evaluation of available energy sources and the identification of low-power communication technologies compatible with indoor optical channels. Commonly deployed white LED luminaires, originally intended for general illumination, typically offer modulation bandwidths in the range of 3 to 5 MHz, making them suitable for supporting low-data-rate VLC [19]. These data rates are sufficient for applications such as smart packaging and environmental monitoring, where sensing updates are periodic and data payloads are minimal. In such scenarios, parameters such as temperature, humidity, or spoilage indicators can be transmitted intermittently without requiring continuous throughput. With the global adoption rate of LED-based lighting projected to exceed 90% by 2030 [20], this widespread infrastructure presents a promising opportunity to repurpose existing luminaires as Optical Access Points (OAP) within the LIoT framework [15–17]. Utilizing the same lighting infrastructure for both illumination and communication reduces hardware redundancy and supports sustainability goals by maximizing the utility of already-installed components, aligning with the environmental requirements of nextgeneration battery-free smart packaging systems. The distributed LIoT nodes in such systems must be capable of performing sensing, OWC, and PVEH under intermittent and variable illumination conditions. Their design aligns conceptually with the ”Smart Dust” vision [21], which envisions ultraminiaturized autonomous devices that integrate sensing, power management, communication, and computation within a highly constrained physical footprint. In applications such as active smart packaging, where compact form factor, energy autonomy, and intermittent updates are critical, these nodes must adhere to zero-energy operation principles. This includes the use of PV-EH modules, energy-aware optical transceivers, and ultra-low-power sensors. The integration of these components enables sustained operation despite fluctuations in indoor light availability and supports intermittent computing when energy resources are insufficient for continuous operation. In order to ensure scalability and deployment practicality, LIoT-ASP node design must also prioritize compactness, cost-efficiency, and environmental compatibility. The use of recyclable materials, printed electronics, and efficient energy conversion interfaces contributes to reducing environmental impact without compromising device capability [15]. In the context of active smart packaging, such considerations are vital for achieving high-volume deployment with minimal ecological footprint. At the system level, the proposed LIoT architecture consists of a centralized OAP and a network of spatially distributed LIoT nodes. Each node operates independently using harvested energy, while the OAP manages coordination, data aggregation, and serves as a gateway to external networks. Fig. 1 presents an overview of this architecture, detailing the primary functional blocks and their interactions within the energy-autonomous LIoT system [15–17]. 3 Design Considerations and Implementation Challenges In general, the design of LIoT systems needs to adhere to the key principles established in our previous work [15–17], including complementing EH architectures, low power OWC strategies, and sustainable component integration. Specifically, energy autonomy can be supported through Harvest-Store-Use 3 Figure 1: Proposed architecture for LIoT-ASP: LED luminaires function as OAPs with gateway connectivity to the broader network. The LIoT node integrates components for OWC, PV-EH, and batteryfree operation. The use of compact and sustainable PE contributes to reduced form factor and improved sustainability. (HSU) protocols in conjunction with multidirectional PV-EH systems, allowing efficient energy capture from ambient illumination regardless of spatial orientation. To ensure reliable communication in complex indoor environments, the use of multidirectional optical transceivers is essential, as they enable omnidirectional reception and help mitigate the limitations imposed by the directional nature of OWC in weak Lineof-Sight (LOS) scenarios. For energy buffering, the use of sustainable electrostatic storage elements, such as Electric Double-Layer Capacitors (EDLCs), which represent the most common class of supercapacitors, offers significant advantages including high cycle stability and reduced environmental impact [22]. Their wide operating temperature range, which is beneficial for applications spanning cold-chain logistics to warm indoor environments, ensures reliable performance of LIoT-ASP systems under varying ambient conditions. Communication can be implemented using single-carrier intensity modulation with direct detection (IM/DD) or similar low-complexity optical schemes suitable for ultra-low-power operation [15]. For low-power operation, it is essential to adopt a duty-cycled design where the node remains in a lowpower sleep mode and transitions to the active state based on either a wake-up trigger from the OAP or a predefined duty cycle schedule. The structure of the LIoT node, comprising the Energy Harvesting Unit (EHU) and the Sensing, Processing, and Communication unit (SPCU), along with the OAP, which includes the main controller and communication interface, is illustrated in Fig. 2, as described in our previous work [15–17]. For LIoT-ASP, it is essential to consider the following discussed design approaches. 3.1 Sustaining Node Operation Under Variable Optical Energy Availability Effective energy storage is a key design consideration in LIoT systems to support reliable operation during low or fluctuating indoor illumination. When determining the appropriate capacitance value Cfor the LIoT-ASP, several factors needs to be considered to ensure continuous functionality. Depending on the operational context, LIoT-ASP nodes may need to maintain functionality during periods when ambient energy is unavailable, such as nighttime conditions when indoor lighting is turned off, or during transport scenarios where illumination may be minimal. In order to support uninterrupted operation, the energy storage unit needs to be capable of sustaining 4 Figure 2: LIoT design structures: (a) LIoT node architecture, (b) optical access point (OAP) architecture [16,17]. the node’s energy demands throughout these intervals. Furthermore, the supercapacitor is expected to deliver sufficient energy for high-demand events, such as sensing operations without causing energy depletion. These operational requirements establish the permissible voltage range for the supercapacitor, represented by [VMin, VMax], over which energy is accumulated and utilized. In order to ensure reliable operation in the absence of PV-EH, the minimum required capacitance can be approximated as follows [23]: CMin ≈ 2EPeak ηEHU,s +PLeakTPeak V2 Max −V2 Min ,(1) where, EPeak denotes the maximum energy required by the node, ηEHU,s is the energy delivery efficiency from the storage element to the system, PLeak is the leakage power associated with the supercapacitor, and TPeak is the maximum duration over which this energy may be consumed. The energy availability condition for executing a sensing task at the ith instance is formalized in (2). This expression ensures that the node has sufficient buffered energy to complete the sensing task without interruption [24]: Esens i≤Ebuf i−Eoper i+ ,(2) where, Esens idenotes the energy required to complete the sensing task, Ebuf irepresents the total buffered energy stored in the supercapacitor at the time of task evaluation, and Eoper iaccounts for the baseline energy required to maintain essential node operation during the task window, such as MCU runtime and peripheral standby. This condition guarantees that the node does not initiate sensing unless there is a sufficient energy margin beyond its operational overhead. By enforcing this constraint, unnecessary power failures and repeated restarts of the same operation due to premature energy depletion are avoided. In the context of LIoT-ASP systems, when a node is triggered by the OAP to perform sensing operations, it must meet the energy availability condition defined in (2), based on the buffered energy Ebuf accumulated at that moment. This requirement ensures that the node has adequate energy to complete the task, thereby preventing repeated execution failures caused by energy outages [25]. In order to mitigate such disruptions, energy-aware control strategies should be employed to evaluate available energy prior to initiating tasks with high energy demand. The node can assess Ebuf by monitoring supercapacitor voltage levels and making informed decisions on whether to proceed with or defer task execution [25]. If the energy level is insufficient, the node may enter a low-power sleep mode to harvest additional energy and resume operation only once the condition in (2) is fulfilled. This forms the basis for an intermittent sensing mechanism, where sensing activities are conducted only when sufficient energy is available [26, 27]. Intermittent execution strategies can generally be divided into two types: best-effort intermittent and soft-intermittent models [28]. In besteffort execution, the node powers on and begins executing tasks immediately after surpassing a predefined activation threshold. It continues operation until the available energy falls below a minimum level, resulting in an abrupt shutdown. On the other hand, the soft-intermittent model initiates task execution only when a target energy threshold is met and allocates a predefined energy budget to complete the task. Before the energy storage level drops below the critical threshold, the system proactively enters sleep mode to minimize power consumption, thereby accelerating energy accumulation from ongoing EH. The energy dynamics of these two approaches are 5 Figure 3: Intermittent operation models: (a) Besteffort intermittent mode, where the node operates until energy drops below the turn-off threshold; (b) Soft intermittent mode, where the node performs tasks within a predefined energy budget and enters sleep mode before reaching the critical energy level. illustrated in Fig. 3, based on models introduced in [28]. For SPCU architectures that rely on volatile memory, the soft-intermittent strategy offers significant advantages. In contrast to best-effort operation, which may lead to loss of execution state upon energy depletion, the soft-intermittent approach allows the system to preserve program states and runtime data by entering a controlled sleep state prior to energy exhaustion. This enhances system stability and responsiveness, particularly in applications that require consistent context retention across multiple power cycles. As a result, soft-intermittent execution is better suited for LIoT-ASP nodes where maintaining execution continuity is essential. To mitigate the risk of energy outages caused by storage depletion, particularly when the capacitor voltage VCap approaches the lower threshold VMin, implementing energy-aware operational strategies becomes essential. Due to their high power density characteristics, supercapacitors inherently exhibit voltage fluctuations during load execution. Consequently, realtime monitoring of the capacitor voltage provides a practical and accurate method for estimating the energy available to the node. If the observed voltage is inadequate to support the execution of the desired task, the node can transition to a low-power state, such as sleep mode, thereby conserving energy and accelerating accumulation from the energy harvester. Although selecting the storage capacitance based on (1) ensures that sufficient energy is available when the capacitor is fully charged, this condition is often not guaranteed in practical indoor environments with limited or inconsistent energy input. Under such conditions, voltage-based decision-making facilitates a smooth transition to intermittent operation modes rather than experiencing a complete operational outage. This strategy supports sustained system reliability and prolongs the operational availability of the LIoT node. A simplified voltage-thresholdbased control mechanism is presented in Algorithm 1 to illustrate this approach. Facilitating coordination between the EHU and the SPCU under continuous energy inflow further enhances resilience, helping to minimize service interruptions and enabling adaptive intermittent operation for energy-constrained LIoT systems. Algorithm 1 Energy availability check based on supercapacitor voltage thresholds Require: VCap (current capacitor voltage), VTask (min voltage required to execute the task), VMin (min voltage threshold to maintain node functionality) 1: VCap ←MeasureVoltage() 2: if VCap ≥VTask then 3: return true 4: else if VCap ≥VMin then 5: EnterSleepMode(short duration) 6: else 7: EnterSleepMode(long duration) 8: end if 9: return false 3.2 Indoor eye friendly Optical Wireless Communication Under Energy Constraints 3.2.1 Low power OWC requirement Consumer IR based OWC demonstrates robust performance in indoor environments, even under the presence of ambient noise and interference. The widespread use in remote control devices for shortrange communication is primarily attributed to the simplicity, energy efficiency, and reliable operation of the technology [29]. These characteristics make consumer IR protocols particularly suitable for portable applications where devices must operate over long durations on limited energy budgets. In the context 6 of LIoT-ASP systems, the uplink typically involves the transmission of low-volume data, such as periodic sensor readings. This limited data requirement aligns well with the capabilities of consumer IR communication, making it a viable reference model for energyaware uplink communication. In these protocols, the transmitter encodes a binary data stream into modulated optical pulses using an IR carrier wave, typically within the 30 to 60 kHz frequency range. The modulated signal is then transmitted using an IR LED emitter, while the receiver demodulates the incoming optical waveform to retrieve the original binary data [30]. Consumer IR systems generally employ Amplitude Shift Keying (ASK) for modulation, with data representation schemes including pulse distance, pulse width, pulse position, and Manchester encoding [29]. The data frame format in typical consumer IR protocols consists of a synchronization header, address bits, and a payload field. The address field allows directed communication between specific devices, while the payload carries commands or sensor data. Although OWC provides inherent physical layer security, vulnerabilities may exist at close proximity. In order to enhance data integrity and confidentiality, optional encryption and authentication mechanisms such as message integrity codes can be integrated, albeit with added computational complexity and longer frame lengths [30]. Several consumer IR standards are applicable to LIoT OWC design. For example, the RC-5 protocol utilizes Manchester encoding with a 36 kHz carrier and a concise 14-bit frame [31]. The NEC protocol employs Pulse Distance Encoding (PDE) with a 38 kHz carrier and supports a 32-bit frame structure [32]. Sony’s SIRC and Panasonic protocols implement pulse width and PDE, respectively, with carriers in the range of 38 to 40 kHz [33, 34]. These standards demonstrate reliable and energy-efficient operation in real-world indoor scenarios, providing proven frameworks for LIoT-ASP OWC implementations. Therefore, exploiting existing consumer IR communication protocols offers a practical and lowpower solution for LIoT systems. Their minimal complexity, reliable performance under typical indoor lighting conditions, and compatibility with energyconstrained operation make them well-suited for the OWC requirements of LIoT-ASP applications. 3.2.2 Eye friendly downlink communication Safe and visually comfortable lighting is a fundamental requirement in indoor VLC environments to ensure user well-being. The IEEE 802.15.7 standard addresses this requirement by incorporating dimming capabilities and ensuring flicker-free operation, even under low-dimming conditions [35,36]. Flicker, characterized by rapid temporal changes in luminance, can adversely affect human perception and performance. In order to mitigate this, the standard introduces the concept of a Maximum Flicker Time Period (MFTP), within which brightness variations must be confined to remain imperceptible [36]. IEEE 802.15.7-2018 recommends the use of visibility patterns and idle pattern transmission to preserve constant illumination during non-communication (interframes) periods. Idle patterns may include in-band signals that are detectable by the receiver or out-ofband signals such as a steady DC bias [36]. Complementary to this, IEEE 1789 [37] outlines recommended practices for modulating high-brightness LEDs to mitigate health risks associated with temporal light modulation. The standard defines Percent Flicker (PF), a key metric in assessing visual comfort and safety, as follows: PF = 100 ×Lmax −Lmin Lmax +Lmin ,(3) where Lmax and Lmin are the maximum and minimum light intensities, respectively. Since the luminous intensity of LEDs in their linear operating region is approximately proportional to the driving current [37], this expression can also be interpreted in terms of current modulation. The relationship between percent flicker and modulation frequency (f) is used to define safety thresholds, as summarized in Table 1. In VLC-based LIoT systems, modulation depth directly influences the signal detectability at the receiver. Higher modulation depth enhances signal strength and improves the signal-to-noise ratio (SNR), thereby lowering the minimum required optical power for successful communication [38]. In order to ensure robust communication in indoor settings, the modulation depth (m) should be optimized while considering transmission distance, path loss, and ambient light interference. The modulation depth is defined as [38]: m=∆I I0 ,(4) 7 Table 1: Percent Flicker Safety Limits Based on IEEE Std 1789-2015 Recommendations [37]. Limit Type Condition Purpose NOEL (No Observable Effect Level) PF < 0.0333 ×f No observable effect; safe for all, including sensitive individuals. LowRisk Level PF <0.08 × f Low probability of adverse biological effects in the general population. Seizure Threshold PF <5% for f≥90 Hz Reduces risk of seizures in individuals with photosensitive epilepsy. where I0is the LED bias current and ∆Iis the amplitude of the modulated current signal. 4 Prototype Development The primary aim of the developed prototype was to monitor the internal temperature of a container and transmit the acquired data to the end user. In addition to sensing functionality, the system supported downlink communication for dynamically updating information on integrated product displays, including parameters such as quality indicators and branding elements. During the component selection and design phase, priority was given to commercially available hardware that supports low-power operation and general-purpose energy-efficient performance. The implemented LIoT node was equipped with a temperature sensor for monitoring ambient conditions. Sensor data was transmitted to the OAP via an IR-based uplink, while display updates were delivered through a visible light downlink channel. The prototype is illustrated in Fig. 4. The OAP was responsible for managing bidirectional communication with the node and was interfaced with the internet through a Wi-Fi module. This setup enabled real-time data transmission to a cloud-based service (ThingSpeak), allowing users to remotely monitor the container’s condition using any internet-enabled device. The graphical user interface for both the webbased dashboard is shown in Fig. 5. 4.1 LIoT-ASP: OAP Design The OAP was developed using a commercially available table lamp housing and standard low-power components, as shown in Fig. 6. A USB-powered DC adapter was employed to supply power to the system, enabling a plug-and-play setup that simplifies on-site deployment and testing. 4.1.1 Main Controller: Processing Unit and LED Driver The main controller unit integrates two MCU platforms for functional partitioning. A Raspberry Pi Pico with Wi-Fi support serves as the internet gateway, handling remote communication and user interface interaction. An Arduino Nano is used for signallevel processing, including data encoding and modulation for optical transmission, as well as reception and decoding of incoming signals. These two MCU communicate over a serial interface, enabling coordination of data transfer and control commands between the cloud platform and the LIoT node. For optical signal modulation, a Series Switch Modulator (SSM) configuration was implemented, following the approach outlined in [39]. The LED driving functionality was realized using an IRF520-based N-channel MOSFET module, which provided fast and energyefficient current switching. 4.1.2 Communication Unit: Illumination Source and uplink Receiver In order to ensure compatibility with both EH and human visual comfort, two types of phosphorconverted white LED arrays were evaluated as downlink transmitters: warm white (3000 K) and cool white (5000 K). These Chip-on-Board (COB) LEDs were directly driven using the modulated output from the SSM circuit. Fig. 7 presents the spectral power distributions of both LED types, measured under a standard indoor illumination level of 500 lux. The results indicate that cool white LEDs emit a broader short-wavelength spectrum, offering a higher photon energy density, which may benefit PV-EH performance. For uplink reception, an Optical Signal Detector (OSD) module based on the KY-022 IR receiver was integrated into the OAP. This module employs a TSOP1833 PIN photodiode with integrated amplification and filtering circuits to ensure robust detection of modulated infrared signals. The TTLcompatible output of the OSD was directly interfaced 8 Figure 4: Implemented PoC LIoT-ASP prototype for smart container applications in supermarket, retail, and storage environments: (a) Prototype LIoT-ASP OAP and node, (b) LIoT-ASP node, (c) Controllable printed-electronics-based display units for indicating product quality index and logo, (d) GUI displayed on a smartphone for wireless control of the OAP. Figure 5: ThingSpeak-based web interface displaying transmitted temperature information accessible via the internet (ThingSpeak Dashboard). Figure 6: Prototype implementation of the OAP incorporating the main controller and communication unit based on the proposed LIoT architecture. with the Arduino Nano, facilitating efficient uplink data acquisition from the LIoT node. 4.1.3 OAP: Operating algorithm The operating algorithm for the PoC OAP is outlined in Algorithm 2. In this implementation, the Raspberry Pi Pico MCU initially receives user commands via Wi-Fi. These commands are then forwarded to the Arduino Nano MCU, which handles communication with the LIoT node. 9 Figure 16: Measured and transmitted temperature variation of the LIoT-ASP container holding dairy products outside the refrigerator. conditions. 6 Conclusion This work presented the design, implementation, and evaluation of a sustainable smart packaging solution based on LIoT architecture, referred to as LIoT-ASP. The proposed system integrates battery-free energyautonomous operation, low-power OWC, and realtime cloud connectivity into a compact and deployable form factor suitable for product condition monitoring. A complete PoC prototype was developed using commercial components, featuring a battery-free node with PV-EH and a dual-mode OAP that supports flicker-free illumination and bidirectional OWC. Experimental results verified the system’s ability to reliably communicate under varying indoor illumination conditions while maintaining compliance with flicker safety guidelines. The use of consumer-grade IR communication protocols and flicker-free VLC demonstrated compatibility with energy-constrained environments, achieving effective FDRs and efficient power utilization. Furthermore, the prototype was validated in a real-world use case involving perishable goods, where temperature deviations were successfully detected and reported via an internet-connected interface. While OWC inherently relies on LOS conditions, which may limit the applicability of the LIoT-ASP concept in scenarios involving occlusion or stacked items, the proposed system is well-suited for deployments where LOS is available, such as on retail shelves or open product displays. In such environments, LIoT-ASP can complement existing technologies, maximizing sustainability benefits through battery-free operation and energy-autonomous active sensing. These results highlight the practical feasibility of deploying LIoT-ASP systems in real-world applications, including smart packaging, retail monitoring, and cold-chain logistics. As future work, lowpower, IoT-friendly OWC protocols can be further optimized to enhance communication robustness by incorporating lightweight error detection mechanisms such as Cyclic Redundancy Checks (CRC), parity bits, or checksums. Additionally, to mitigate challenges arising from non-LOS scenarios, the feasibility of using Optically Reconfigurable Intelligent Surfaces (O-RIS) can be explored as a potential solution. Furthermore, the reliance on conventional electronic components can be reduced by utilizing existing PV cells for both EH and OWC reception, enabling a more compact and energy-efficient node architecture. To further improve integration and reduce hardware complexity, the EHU and the SPCU can be consolidated into a System-On-Chip (SoC) platform, enhancing overall system efficiency and compactness while further minimizing the use of conventional electronic components. In addition, developing a middleware management layer that interfaces between distributed LIoT-ASP nodes and facilitylevel control systems could enhance scalability, interoperability, and real-time decision-making. Such a layer would facilitate seamless integration of LIoTASP into existing cold chain and retail infrastructure, enabling dynamic optimization of operations based on LIoT-ASP insights. This can support energyaware facility management, reduce operational costs such as electricity usage, and strengthen sustainability across the supply chain. Overall, the proposed LIoT-ASP design and framework presents a feasible and scalable approach to sustainable IoT system design, enabling battery-free, light-powered active monitoring through smart packaging. This approach reduces product waste, enhances supply chain visibility, and promotes environmentally responsible practices in next-generation IoT-enabled packaging and logistics applications. Acknowledgment This work was supported by 6G Flagship (Grant Number 369116) funded by the Research Council of Finland, and the SUPERIOT projects. 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